Research Report: Constellation Cosmos™
Evaluating Four Vendor Solutions for Managing
Data Growth
Constellation’s Cosmos:
Data Archiving Solutions
By Dr. Alea Fairchild
Vice President and Principal Analyst
Content Editor: R “Ray” Wang Copy Editor: Maria Shao
Table of Contents
Purpose and Intent ... 4
Executive Summary ... 4
Importance of Data Archiving: Age of Big Data and Technology Optimization ... 6
Application Retirement ... 7
Database Performance Optimization ... 7
Legal Performance ... 7
Trends in Data Archiving from This Evaluation ... 7
Brief Overview of Evolution of Data Archiving ... 8
Research Methodology ... 9
Constellation CosmosTM Overview ... 9
Vendor Inclusion Criteria ... 10
Overview of Evaluation Criteria ... 10
Vendor/Analyst Comparative View ... 11
Differentiators ... 11
Results – Vendor Overview ... 12
Solix and Informatica Lead in Ownership Experience ... 13
IBM and Informatica Lead in Market Execution ... 14
IBM and Informatica Lead in Corporate Vision ... 15
Informatica Leads in Ecosystem Feedback... 16
Results – Solution Overview ... 17
IBM, Informatica and Solix Lead Close Race in Application Support and Experience ... 18
IBM, Informatica and Solix Well-Matched in Functional and Technical Requirements .... 20
Informatica Leads in Business and Legal Requirements... 21
Use Cases Definitions ... 23
Cosmos Ratings for the Use Cases ... 24
Constellation’s Cosmos ... 25
Application Retirement ... 25
All Four Vendors Achieve EPIC Status ... 25
Improving Database Manageability ... 26
HP Demonstrates Stellar Solutions ... 26
Operational/Storage Cost Savings ... 26
IBM, Informatica and Solix Achieve EPIC Status ... 26
HP Demonstrates Stellar Solutions ... 27
Performance Archiving ... 27
Solix, Informatica and IBM Achieve EPIC Status ... 27
HP Demonstrates Stellar Solutions ... 27
Recommendations ... 28
Analyst Bio: Dr. Alea Fairchild ... 29
Disclosures ... 29
About Constellation Research ... 30
Purpose and Intent
Why are data archiving solutions important for today’s enterprise data management strategies?
Techniques for information lifecycle management are changing; data is now viewed more as a business object than as transactional data elements.
Data’s role in the enterprise is mission critical to enterprise health, both positively in terms of competition, and negatively in terms of compliance and regulatory pressures.
Big Data and exponential growth in the amount of information required to store and manage require a data growth strategy, in which data archiving is a critical element for success.
Data archiving has evolved over the years from having an application-oriented focus (i.e. application performance enhancement) to having a storage focus (i.e. data location for regulatory reasons) and, now, to having a focus on the value to the business of the data, thus elevating the importance of stewardship over how the data should be held, treated and disposed. To rationalize resource and application investment, data archiving strategies are critical to technology optimization efforts.
In today’s enterprise, a well-structured data archiving strategy can help lower Information Technology (IT) costs, improve application performance and enhance data security. We therefore have assessed four of the top data archiving solutions in order to provide an overview of the market for user evaluation. This report offers management insights into one of Constellation’s primary research themes, Technology Optimization.
Executive Summary
Given the exponential growth of data in the enterprise and the continued need to manage, regulate and maintain this data, this report assesses some of the top offerings in the data archiving market to assist enterprises in making strategic decisions on how to manage data growth. Technology optimization creates a need to reduce costs as well as to optimize database content to enhance performance.
Although we did make functional comparisons among the products, what is equally important here are the drivers and use cases for data archiving technologies. These solutions also can be used to consolidate applications as part of a renewal and retirement process for technology that enhances innovation. Increasing rates of application retirement and the increasing requirements in compliance and e-discovery have caused enterprises to take a closer look at data archiving.
We surveyed vendors, users and systems integrators on six sets of criteria, involving market execution and user experiences, as well as solution criteria and vendor resources. We found a very close race, where the focus has changed from more technical criteria to better data planning via data usage and growth analysis; simulation of archive policies,
including preview of data prior to archiving and purging; and process management via a centralized view across multiple applications, databases and operating systems.
Among the trends we saw: data archiving is seen as a stand-alone feature despite a broader Information Lifecycle Management (ILM) footprint, and data masking remains a critical feature, due to privacy concerns. Archiving solutions have been historically designed for IT departmental managers; now the need is for wider customer usage. Cloud has affected the business model, with users indicating significant interest in Archiving as a Service (AaaS). Enabling access to older data without maintaining the retired application is a key driver for data archiving, making possible cost savings and operational audit abilities.
Importance of Data Archiving: Age of Big Data
and Technology Optimization
Data growth is happening at a rate we couldn't have imagined a few decades ago. To prepare for a successful future, businesses need to work to protect data assets as they grow exponentially. Data archiving has changed dramatically in the last three years, as explosive data growth and the maturity of database applications have meant a shift from structured data management to significant movements of all types of data to both on-premise and off-on-premise (cloud) locations.
The concept of data archiving was initially driven by an emphasis on application management and a focus on protecting production data. The focus then shifted in the last few years -- based on the vast amounts of structured and unstructured data and their corresponding rules -- to data storage and then to regulatory compliance. Data archiving solutions need to be accessible and user-friendly to people beyond the IT department. Business drivers for data archiving include compliance requirements (data retention and security), necessary service levels (performance and availability) and cost reduction (server and storage consolidation, media costs and management/staffing costs) (See Figure 1).
Figure 1. Drivers for Data Archiving Strategy
Why have we chosen to compare offerings of data archiving solutions?
Enterprise database applications are critical to business success, and the handling of the data assets is necessary for audit and regulatory policy.
Technology optimization creates a need to reduce costs but optimize databases to enhance performance. Feature/function comparisons don’t tell the complete picture in this regard. Adaptable data storage for business agility Continuous data availability to the business Productivity and efficiency in data archiving Cost controls on data infrastructural growth
E-discovery and legal compliance make ease of locating and selecting data imperative to supporting the business.
Application Retirement
With cost and resource constraints, enterprises need to have a retirement strategy to remove legacy applications from use while retaining access to the data without the cost and effort of maintaining the older applications. When taking applications out of service, companies need to consider the ongoing legal requirements for data access and the impact decommissioning can have on other applications.
Database Performance Optimization
As database size increases, the performance of these applications deteriorates. The larger the database, the more time it takes to load, search, reorganize, index and optimize. Adding to this problem is the fact that a significant amount of this data can be inactive or infrequently accessed. If data can be removed and archived appropriately, performance increases and service levels can be maintained.
Legal Performance
Data is potentially discoverable in court if it is relevant to a disputed transaction. Preservation of data for e-discovery has become a complicated, changing concept in recent years. The “legal hold” process is often equated to the herding of cats, as it is necessary to maintain all relevant information when litigation might be anticipated. The volumes of data which may need to be preserved in multiple global locations, platforms and formats make automation of the process critical.
Trends in Data Archiving from This Evaluation
Based on extensive evaluation of the products, references from customers and conversations with system integrators, Constellation Research has identified the following six trends:
1. Data archiving is seen as a stand-alone feature despite a broader ILM footprint. Three of the four vendors assessed acquired their archiving technology from an Independent Software Vendor (ISV) and integrated it into their wider Information Lifecycle Management (ILM) systems. However, users interviewed had not always acquired the whole ILM package, as some still saw data archiving as a stand-alone feature.
2. Data masking remains a critical feature. Both reference customers and Constellation Research clients pointed out that data masking is still important. They wanted confidential and sensitive information, such as Personally Identifiable Information (PII), Payment Card Industry (PCI), and Personal Health Information (PHI) concealed within the data elements. This is also the case for production data
testing, since real-life proprietary information from company operations is typically used.
3. Archiving must move beyond the IT department and into the hands of business users. Historically, archiving solutions have been designed for IT managers. Now, the customer audience is wider. Unfortunately, not all vendors have addressed this well. Some still focus on the features more attractive to an IT engineer than a lawyer or product manager.
4. Buyers indicate significant interest in Archiving as a Service (AaaS). Enterprises are more frequently considering AaaS (or cloud archiving) as a solution for their ongoing data management challenges. These new models deliver interaction and presentation, and map back to the Open Archival Information System (OAIS) information package standards.
5. File archiving continues as an option in an era of Big Data. File archiving has led the trend for other forms of archiving, such as e-mail and databases. File archiving for very large volumes of data is emerging as a growth option for enterprises that previously added more disks to deal with data growth. Throw in the cloud, and you have the makings of a new business model for archiving, both in terms of usage and licensing.
6. Application retirement is a key driver for enhanced strategies. Enabling access to older data without maintaining the retired application is key for both cost savings and operational audit.
Brief Overview of Evolution of Data Archiving
This market has evolved from the initial database archiving products of companies such as Outerbay, Princeton Softech and Applimation, all acquired by the vendors compared in this report. As the amount of data that must be retained skyrocketed, data archiving became more of a physical storage strategy, then evolved to focus on business value as compliance and data leakage (data loss resulting from employee behavior, for example) became drivers.
Data archiving is a procedure embedded in the business processes of the enterprise (See Figure 2). The way it is implemented depends on the value and role of the data in the enterprise and its business. Data Lifecycle Management depicts how that value changes over time, based on usage and application. The fresher the data and closer to active use, the higher the value. As data gets older, its value diminishes, but it never becomes worthless. The long tail at the end shows that data never becomes truly obsolete, but can have a negative impact on value if not retained (i.e. regulatory fines and litigation).
Figure 2. Performance Archiving Critical to Data Lifecycle Management
Research Methodology
Constellation Cosmos
TMOverview
Constellation CosmosTM is Constellation Research’s flagship quantitative and qualitative product and solution comparison tool. A typical Cosmos contains 50 to 150 exception-based criteria used to help buy-side clients with product and solution selection across the galaxy of choices. The evaluation consists of six major categories where Constellation Research evaluates key criteria on a 0 to 5 point scale, with 0 being the lowest and 5 being the highest:
1. Ownership experience. Criteria include vendor executive advocacy and accountability, timely and meaningful interactions, professional customer support, overall sales cycle and buying process, quality of product and service and ongoing transparency.
2. Solution offering. Criteria include functional requirements, technical requirements, architectural considerations and deployment options.
3. Use case support. Criteria include the ability to support anywhere from three to 12 popular use cases requested by end users. Use cases typically align with business processes. Considerations include geographical requirements, market size requirements and industry requirements.
4. Market execution. Criteria include the number of live customers, customers including prospects, customers over $1 billion in revenue, externally trained professional service staff, internally trained professional service staff, updates per year; amount of funding raised to date (if a start-up); annual revenues; and geographic penetration. Data creation Data operational usage Active data retention Archived active data Archived unused data Long-Term storage for compliance D ata Val u e
Performance Archiving: Data Lifecycle
Management
5. Corporate vision. Criteria include the strength of the management team, product direction, level of innovation, market leadership, community stewardship and investment in research and development.
6. Ecosystem feedback. Criteria include vendor-supplied references (at least three), direct customer feedback from inquiries and interactions and partner feedback.
Vendor Inclusion Criteria
This edition of the Data Archiving solutions evaluation includes vendors who: Offer a full-featured data archiving solution.
Service customers that require significant Enterprise Resources Planning (ERP) and Customer Relationship Management (CRM) packaged and custom application support.
Support use cases in application retirement, database manageability and legal performance issues such as support for legal hold and e-discovery.
Based on the above criteria, Constellation Research evaluated four solutions from the following vendors (Version and General Availability, or GA, are noted):
HP Database Archiving Software, v6.3 (v6.4 will be GA this fall) IBM InfoSphere Optim Data Growth Solution, v 8.1
Informatica Data Archive, Advanced Edition
Solix Enterprise Data Management Suite (EDMS) 5.5
Other vendor solutions not evaluated in this report include Opentext. However, this solution was seen to function more in the area of web content management.
Overview of Evaluation Criteria
Constellation Research evaluated solutions on six sets of criteria. Details on the weighting factors for the evaluation are stated below (See Figure 3):
Figure 3. Weighting Criteria Emphasize Solution Offering and Use Case Support
Data Archiving Weighting of Criteria
Ownership experience 10%
Solution offering 36%
Market execution 10%
Corporate vision 10%
Ecosystem feedback 10%
Vendor/Analyst Comparative View
Each of the four vendors was provided the sets of criteria on which to comment, and they provided detailed feedback on how they specifically met these criteria, if applicable. Although HP did provide a briefing on its solution, HP did not provide much information on the feedback sheet and the analysis of the criteria was performed by the analyst instead, based on the materials provided the company. The analyst also cross-checked all vendor responses with the materials and with the user interviews for clarity.
Differentiators
Approximately 80 percent of the technical features offered by all the data archiving vendors are similar; therefore, we try to focus on differentiators. Here, we share our analysis, based both on the vendor briefings and on the user interviews, as to what makes these particular vendors unique in this space (See Figure 4):
Figure 4. Constellation Identifies Key Differentiators among Four Solutions
HP HP’s Database Archiving (DBA) solution comes from its Information Management division, which incorporates the acquisition of Autonomy. The unique ability to search and create a dynamic schema model to manage the back-end target comes from the Autonomy Intelligent Data Operating Layer (IDOL) Universal Search functionality. Legal teams find the HP DBA product positive in terms of ease of use for legal hold. HP claims a more holistic approach, citing strength in records management and its treatment of data as a business document.
IBM Of the four solutions, IBM InfoSphere Optim is the most sophisticated in terms of development for data lifecycle management and granular business object detail. With a business object approach to defining and maintaining the data, the solution has a strong focus on data growth strategies that serve business needs. IBM InfoSphere Optim is designed on optimization of data usage, with an emphasis on scalability and integration across databases.
Informatica Informatica has the broadest range of integration into packaged and custom applications. Its focus is on managing data growth by moving inactive data out of the production database. Informatica has a strong focus on application retirement solutions and provides non- IT, user-friendly tools to ensure compliance with database archiving.
Solix This solution was developed for the database archiving market and remains well-focused in this area. Although a smaller company, Solix’s close cooperation with the enterprise customer was highly appreciated from the user feedback in our report. The focus on reduction of operational cost and optimization of enterprise data accessibility were strong points from our interviews.
Results – Vendor Overview
The chart below shows how each vendor stacked up in the six criteria segments. The lowest possible score is 0 and the highest is 5. The ratings were derived from user interviews, vendors’ responses to Constellation Research questionnaire and product information supplied by vendors. (See Figures 5 and 6)
Figure 5. Overall Scores for Four Data Archiving Vendors
HP IBM Informatica Solix TOTAL 4.12 4.76 4.76 4.55
1. Ownership Experience 3.75 4.30 4.38 4.48
2. High Level Use Case Support 4.13 4.78 4.90 4.90
3. Solution Offering 4.37 4.69 4.70 4.54
4. Market Execution 3.85 4.85 4.25 3.35
5. Corporate Vision 3.45 4.60 4.33 4.20
6. Ecosystem Feedback 3.25 4.10 4.60 4.00
Solix and Informatica Lead in Ownership Experience
Solix succeeded well in this category, offering close cooperation with customers and accessibility of senior management for feedback and executive advocacy.
Informatica has put in place an ILM business unit, and key executives and management in the business unit must meet targets/goals based on customer success and satisfaction in the Data Archive and Data Privacy product areas, with a priority on the appropriate accountability assigned on ability to execute (See Figures 7 and 8).
IBM InfoSphere Optim has a Client Advocate Program (CAPO) designed to monitor customer satisfaction. This is structured to be a “safety net” for customers’ success. HP is currently going through a transition period, with lots of acquisitions to integrate and, therefore, communication with the customer is not seen as optimal. HP provided the least information among the four vendors studied.
Figure 7. Solix and Informatica Lead in Ownership Experience
HP IBM Informatica Solix
TOTAL 3.75 4.30 4.38 4.48
Vendor executive advocacy and accountability 4.00 4.50 5.00 4.00
Timely and meaningful interactions 3.00 4.00 4.50 4.00
Professional customer support 3.00 4.50 4.50 4.50
Overall sales cycle and buying process 4.00 4.50 4.00 4.00
Deployment ease 4.50 4.00 4.00 5.00
Quality of product and service
updates/upgrades 4.00 4.50 4.00 5.00
Ongoing transparency of communications 3.00 4.00 4.50 4.00 Figure 8. Solix and Informatica Lead in Ownership Experience
IBM and Informatica Lead in Market Execution
IBM holds a clear leadership position in this category, due to investment in patented technology, people and resources (See Figures 9 and 10). Informatica comes in a strong second, enhanced by strong partner relationships. Solix, given its size, would require more partners and manpower to potentially reach a higher level. HP has had issues with staffing and realignment of resources post-acquisitions.
F
igure 9. IBM and Informatica Lead in Market ExecutionHP IBM Informatica Solix
TOTAL 3.85 4.85 4.25 3.35
Total number of live customers 4.00 5.00 4.00 3.00
Total number of customers including prospects 4.00 5.00 5.00 4.00 Total number of customers over $1B in revenue 5.00 5.00 4.00 2.00
Total annual revenues 3.00 5.00 5.00 4.00
Total number of externally trained professional service
staff 3.00 5.00 3.00 3.00
Total number of internally trained professional service
staff 3.00 4.00 3.00 2.00
Number of updates per year 4.00 5.00 5.00 4.00
Geographic penetration 5.00 5.00 5.00 5.00
IBM and Informatica Lead in Corporate Vision
IBM and Informatica have made significant investments in their ILM portfolios, as has HP, although HP is still digesting some of its more recent ILM investments. Solix has clearly articulated its vision to customers, but its rating may be limited by its stature as a David while the other vendors are Goliaths (See Figures 11 and 12).
Figure 11. IBM and Informatica Lead in Corporate Vision
HP IBM Informatica Solix
TOTAL 3.45 4.60 4.33 4.20
Strength of management team 4.00 5.00 4.50 4.00
Product direction 4.00 5.00 4.50 4.00
Level of innovation 4.00 4.50 4.50 5.00
Market leadership 3.00 5.00 4.00 4.00
Community stewardship 3.00 5.00 4.00 4.00
Investment in R&D 1.00 2.00 4.00 4.00
Informatica Leads in Ecosystem Feedback
Each solution vendor provided a number of reference accounts and channel partner details, and interviews were done with these enterprises, as well as Constellation Research panel members who have experience with these solutions.
Informatica has the highest rating from users and partners, with a number mentioning the breadth of integration with applications and a strong ecosystem of partners. (See Figures 13 and 14) Solix also has very close relationships with its enterprise customers, and is seen as very responsive to requests and feedback. IBM incorporates both formal and informal mechanisms for communication, but is still seen as a large organization with hierarchies and complex processes. HP, with its transitionary period, is viewed as not so transparent in its communication.
Figure 13. Informatica Leads in Ecosystem Feedback
HP IBM Informatica Solix
TOTAL 3.25 4.10 4.60 4.00
Vendor supplied references 3.00 4.00 4.50 4.00
Direct customer feedback 3.50 4.00 5.00 4.00
Partner feedback 4.00 5.00 4.00 4.00
Key: 5 = Very positive
4 = Positive 3 = Neutral
Figure 14. Informatica Leads in Ecosystem Feedback
HP IBM Informatica Solix 0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 4.00 4.50 5.00 Vendor supplied references Direct customer feedback Partner feedback HP IBM Informatica Solix
Results – Solution Overview
The four solutions also were rated on how well they met functional, technical, business and legal needs of end users as well as how they worked with applications. (See Figures 15 and 16) Informatica and IBM were virtually tied. Solix came close behind, followed by HP.
Figure 15. Summary of Three Solutions Categories
HP IBM Informatica Solix
TOTAL 4.37 4.69 4.70 4.54
Applications Support and Experience 4.35 4.85 4.70 4.70 Functional and technical
requirements 4.20 4.75 4.70 4.65
Business and Legal Requirements 4.55 4.48 4.70 4.28
IBM, Informatica and Solix Lead Close Race in Application
Support and Experience
Key areas of competitiveness in this space included pre-packaged application metadata, client and web architecture deployment and data usage and growth analysis. (See Figures 17 and 18)
Figure 17. IBM, Informatica and Solix Lead Close Race in Application Support and Experience
HP IBM Informatica Solix
TOTAL 4.35 4.85 4.70 4.70
Breadth and depth of pre-packaged
application metadata and business rules 4.50 5.00 5.00 4.50
Breadth of relational database connectivity 4.00 5.00 5.00 5.00 Breadth of mainframe and legacy application
connectivity 4.00 5.00 4.50 4.00
Breadth of client and web architectural support (deployment models)
4.50 5.00 4.50 4.50
Storage efficiency - compression ratio 4.00 4.50 5.00 4.50
Breadth of platforms (storage, OS) supported 5.00 5.00 5.00 5.00
Load and query performance 4.00 4.50 4.00 4.00
Ability to easily develop packaged application
support natively 4.00 5.00 4.00 5.00
Ability to generate archive candidate reports for the business
5.00 4.50 4.50 4.00
Automatically manage schema change in
archive 5.00 4.50 4.50 5.00
Data usage and growth analysis 4.00 5.00 5.00 5.00
Figure 18. IBM, Informatica and Solix Lead Close Race in Application Support and Experience
IBM, Informatica and Solix Well-Matched in Functional and
Technical Requirements
Key areas of competitiveness in this space included maintenance of data integrity, other access methods to archived data and granularity of restore. (See Figures 19 and 20)
Figure 19. IBM, Informatica and Solix Well-Matched in Functional and Technical Requirements
HP IBM Informatica Solix
TOTAL 4.20 4.75 4.70 4.65
Index and search ability 5.00 4.50 4.50 4.50
Archive to another database or archive to file format 4.00 5.00 5.00 4.50
Maintain data / referential integrity 4.00 5.00 4.50 4.00
Seamless access from original application and from
any reporting / BI tool 4.00 4.00 5.00 5.00
Other access methods to archived data 5.00 4.50 4.50 5.00
Integration to user authentication, such as LDAP, AD
and SSO 4.00 5.00 5.00 5.00
Security to prevent unauthorized changes to the
archived data 4.00 5.00 4.50 5.00
Scalability - can handle larger volume sets 4.00 5.00 5.00 4.50
Granularity of restore 4.00 4.50 4.50 4.00
Flexibility (same meta data, different app
deployment) 4.00 5.00 4.50 5.00
Figure 20. IBM, Informatica and Solix Well-Matched in Functional and Technical Requirements
Informatica Leads in Business and Legal Requirements
Key areas of competitiveness in this space included legacy application retirement stages, audit of access to archive, masked data sharing and support for legal hold. From this section, it is clear data archiving has evolved into a process that supports the business value of the data. (See Figures 21 and 22)
Figure 21. Informatica Leads in Business and Legal Requirements
HP IBM Informatica Solix
TOTAL 4.55 4.48 4.70 4.28
Legacy app retirement cycle stages 4.50 4.00 4.00 4.50
Immutability of archived data 4.00 4.00 5.00 4.00
Audit of access to archive 4.00 3.50 5.00 4.00
Monitoring of database activity 4.00 4.50 4.00 3.00
Discovery of data relationships 5.00 5.00 5.00 4.00
Speed of access to historical data for e-discovery
5.00 4.50 4.00 4.00
Masked data sharing 4.50 4.50 5.00 4.00
Data discovery, search based on business entities
5.00 5.00 4.50 4.00
Retention management and purging based on retention expiration
4.50 5.00 5.00 5.00
Support for legal hold 5.00 5.00 5.00 4.00
Role based access / security policy
automation for archived materials 4.00 4.50 5.00 5.00
Archiving of attachments (database or file
system) 4.00 4.00 4.50 5.00
Use Cases Definitions
Constellation Research’s methodology includes the evaluation of the solution using real-world use cases. Here are the descriptions of the four use cases:
Application retirement: Use case on the decommissioning of applications that are no longer mandatory to support business operations.
Improving database manageability performance: Use case on improving database application manageability, significantly increasing performance for enterprises with accelerating data growth.
Operational/storage cost saving: Use case focused on cost reduction, improved operational efficiencies, business reuse and risk mitigation.
Performance archiving: Use case on the practice of managing data that makes decisions based upon the effect of time on the probability of access.
Figure 24. Description of Use Cases
Cosmos Ratings for the Use Cases
Epic: Composite scores above 4.5 will be rated in this highest category.
Stellar: Composite scores between 3.5 and 4.49 will be rated in this second category
Emerging: Composite scores between 2.5 and 3.49 will be rated in this third category
Nascent: Composite scores between 1.5 and 2.49 will be rated in this third category
Laggard: Composite scores between 0 and 1.49 will be rated in this fourth category
Constellation’s Cosmos
Figure 25. Cosmos Use Cases Focus on Performance and ROI
HP IBM Informatica Solix
TOTAL 4.13 4.78 4.90 4.90
Performance archive use cases (ROI) 4.00 4.50 5.00 5.00
Application retirement use cases (ROI) 4.50 5.00 5.00 5.00
Operational/storage cost saving use case (ROI) 4.00 4.50 4.50 4.50 Improving database manageability performance
(ROI) 4.00 5.00 5.00 5.00
Application Retirement
All Four Vendors Achieve EPIC Status
Although it may seem odd that all solution vendors scored highly, this result is not so surprising, given the strong focus on application retirement in the current market situation. A strong focus on efficiency, application retirement assessment and easy access to retired data are the drivers for this usage.
HP has a Wizard intended to accelerate application retirement by making the process more automated, and HP archives the data to an XML archiving solution. IBM InfoSphere Optim focuses on supporting long-term retention compliance and
reducing risk. IBM also discovers the entire data model across the enterprise (across multiple platforms/applications) consistently and robustly. This archived data is accessible independent of the original application, and can be stored to a variety of storage media, based on business value and access requirements.
Informatica also has a full-featured application retirement wizard that includes discovering the data model for the application to be retired. Using the data validation option, data in the archive is compared to the source to ensure all data has been archived without error. Data retention policies are then defined based on corporate retention policies. Data in the file archive can be viewed, leveraging any reporting tool with ODBC/JDBC connectivity and additionally leveraging Informatica's Data Discovery portal.
Solix EDMS Application Retirement is part of the Solix EDMS platform and provides out-of-box support for end-to-end application retirement processes that can be designed-deployed-maintained-managed from a single platform. Once the data is available in the archive, seamless access can be provisioned to end users based on role-based security and access, ad hoc query, report creation and sharing through Solix Application Portfolio Manager (APM). Power users can create the ad hoc reports and share them with other users. The data in the archive can be further
regulated based on retention policies, data disposition with the ability to enforce legal holds on data as required.
In this category, there were no stellar, emerging, nascent and laggards.
Improving Database Manageability
Reducing the size of the database, as well as tiering data storage in line with business value, are some of the drivers for this usage.
IBM, Informatica and Solix Achieve EPIC Status
IBM InfoSphere Optim focuses on automating the archive capabilities to allow different archive processes to manage data growth across multiple business areas. By automating the archive capabilities with highly compressed archive files, firms achieve stability and reliability in the production environment, while improving service levels due to faster application response times.
Informatica believes that partitioning provides performance benefits without having to archive data out of the production database. Archiving data to an archive file that is highly compressed also delivers ease of manageability as the database can be managed with near-zero data growth rates.
Solix can archive information into a partition or an archive database and then, based on retention policies, move data into a file-based archive or Solix Cloud. Finally, it can dispose of the data based on policy. Solix has the ability to support multiple use cases and deployment models (on-premise, on-cloud) with a single platform that is easy to deploy and manage.
HP Demonstrates Stellar Solutions
HP Database Archiving solution allows data to be relocated to a separate, online database for fast, transparent access or to standards-based XML or CSV documents for long-term retention. HP’s solution includes an integrated set of components that facilitates design and deployment throughout the lifecycle of applications and data. In this category, there were no emerging, nascent and laggards.
Operational/Storage Cost Savings
With cloud, database outsourcing, and tiered data storage parameters, capital expenditures reduction and operational efficiency are a few of the drivers for this usage.
IBM, Informatica and Solix Achieve EPIC Status
IBM InfoSphere Optim focuses on creating a consistent, repeatable process for archiving data, thereby reducing the quantity of data in the production environment.
Informatica customers can either leverage smart partitioning or archive to a separate database. When data has been archived out of the production database to either a separate database or a file archive, organizations realize storage savings when copies of production are refreshed. That’s because the data that has been archived is no longer copied. This is also the case for organizations taking advantage of smart partitioning, where only active partitions are copied for test and development purposes.
Solix EDMS Test Data Management leverages the core metadata services in Solix EDMS to deliver very small database subsets that will improve operational efficiencies and storage savings.
HP Demonstrates Stellar Solutions
HP focuses on organizing, classifying and managing e-mail, documents and physical records for operational storage size reduction. HP Database Archiving software supports a three-tier archive strategy. Data is relocated from the
production database to either the online archive via database-to-database archiving or to the XML store via database-to-XML archiving.
In this category, there were no emerging, nascent and laggards.
Performance Archiving
Solix, Informatica and IBM Achieve EPIC Status
Solix has a unique differentiator with its recent cloud archiving release, which can be included in a performance archiving strategy.
Informatica offers several integration options to ensure organizations are achieving significant performance benefits due to archiving. Informatica offers two editions: Data Archive Standard and Advanced. By either partitioning or archiving data out of the production database, application performance is drastically improved. For some custom applications, configuration may be required to ensure the discovered data model is complete and accurate from an archiving or partitioning perspective.
IBM defines business objects in order to assign an application data record – e.g. payment, invoice, customer tied to a business activity, instead of focusing on transaction records.
HP Demonstrates a Stellar Solution
HP is strong in records management, using its TRIM solution. HP can do simulation of the archive before the actual archiving takes place, so the results can be foreseen and evaluated before data is committed.
Recommendations
Constellation Research recommends that users and prospects invest in a data growth management strategy that enables proactive investment decisions on data location and preservation. Select the solution partner that best fits your needs for database archiving, e-discovery tools, application retirement and data masking.
For service performance-sensitive scenarios: If data needs to be accessed throughout regular operations, focus on a solution provider that tiers the data and uses the solution to be service performance-sensitive. Informatica has a high degree of integration with other packages and IBM is also well-known for using an information governance lens in its approach to data needs, thus helping organizations manage performance of data throughout its lifecycle.
For those seeking cloud offerings: The enterprise can proactively plan infrastructure and technology purchases that will facilitate efforts to control data growth. If cloud is on the horizon, focus on a solution vendor that is facilitating data transfer to the cloud. Solix has highlighted its new cloud offering and cloud efforts as part of our analysis.
For those seeking a user-friendly approach to business objects: As data access requirements drop over time, the criticality of the data changes. By mapping out business users’ access needs over time, it is easier to meet legal or records management retention schedules and operational support needs. IBM, with its use of Open Database Connectivity (ODBC), has a user-friendly approach to business objects. HP is also rules-oriented and implements the IDOL schema from its acquisition of Autonomy.
The choice of solution can also depend on a number of variables:
Size of company. Some enterprises want to work with a vendor of a similar stature. Others prefer a high level of expertise from the vendor, but want the implementation done by a third party systems integrator.
Technology. Depending on databases leveraged (e.g. Oracle Database, DB2, Informix), packaged applications in use (Oracle E-Business Suite, PeopleSoft Enterprise, Siebel CRM) and technology preferences (JDBC, ODBC, SQL), certain solutions may be a better fit than others.
Type of data archiving management issue. If the driver is application retirement, the scalability and accessibility to archived data become critical. If, on the other hand, compliance and audit ability are driving the decision, the interface and tools needs to be usable by a non-IT audience.
Analyst Bio: Dr. Alea Fairchild
Data Management and IAM Analyst
Dr. Alea Fairchild is a Vice President and Principal Analyst at Constellation Research and a Director at the Constantia Institute bvba. She is also a Professor on the Faculty of Economics and Management at Hogeschool-Universitair Brussel.
She was previously a Senior Researcher at Tilburg University in the Netherlands in the Department of Information Management. Her technical expertise lies in open architectures and interoperability. Recent areas of research have included knowledge management and productivity metrics for technology. Her academic training is in the area of information economics.
Dr. Fairchild has 18 years of experience in global IT market analysis, and has worked for major market research firms as both an analyst and as a consultant. She has also been a consultant to the European Commission as well as to major multinational IT companies throughout Europe. She is the author of several conference papers and articles and of five books: “Interoperability for Enterprise Information Systems”, September 1996; “Year 2000 Compliance: The Guide to Successful Implementation,” May 1997; and "Reengineering and Restructuring the Enterprise," February 1998, all published by CTR. Her book, “Technological Aspects of Virtual Organizations”, was published by Kluwer and her latest book, “Entrepreneurship: Introduction to Business Plans”, was published by die Keure.
Dr. Fairchild received her Doctorate in Applied Economics from Limburgs Universitair Centrum (now Universiteit Hasselt) in Belgium.
Dr. Fairchild can be reached at [email protected].
Disclosures
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