by Doug Dailey
Editorial Note: IBM Fluid Query 1.7 became available in May, 2016. You can read about features in release 1.6 here, but we also recommend reading the release 1.7 blog here.
The IBM PureData Systems for Analytics team has assembled a value-add set of enhancements over current software versions of Netezza Platform Software (NPS), INZA software and Fluid Query. We have enhanced integration, security, real-time analytics for System z and usability features with our latest software suite arriving on Fix Central today.
There will be something here for everyone, whether you are looking to integrate your PureData System (Netezza) into a Logical Data Warehouse, improve security, gain more leverage with DB2 Analytics Accelerator for z/OS, or simply improve your day-to-day experience. This post covers the IBM Fluid Query 1.6 technology. Refer to my NPS and INZA post (link) for more information on the enhancements that are now available in these other areas.
Integrating with the Logical Data Warehouse: Fluid Query overview
Are you struggling with building out your data reservoir, lake or lagoon? Feeling stuck in a swamp? Or, are you surfing effortlessly through an organized Logical Data Warehouse (LDW)?
Fluid Query offers a nice baseline of capability to get your PureData footprint plugged into your broader data environment or tethered directly to your IBM BigInsights Apache Hadoop distribution. Opening access across your broader ecosystem of on-premise, cloud, commodity hardware and Hadoop platforms gets you ever closer to capturing value throughout “systems of engagement” and “systems of record” so you can reveal new insights across the enterprise.
Now is the time to be fluid in your business, whether it is ease of data integration, access to key data for discovery/exploration, monetizing data, or sizing fit-for-purpose stores for different data types. IBM Fluid Query opens these conversations and offers some valuable flexibility to connect the PureData System with other PureData Systems, Hadoop, DB2, Oracle and virtually any structured data source that supports JDBC drivers.
The value of content and the ability to tap into new insights is a must have to compete in any market. Fluid Query allows you to provision data for better use by application developers, data scientists and business users. We provide the tools to build the capability to enable any user group.
What’s new in Fluid Query 1.6?
Fluid Query was released this year and is in its third “agile” release of the year. As part of NPS software, it is available at no charge to existing PureData clients, and you will find information on how to access Fluid Query 1.6 below.
This capability enables you to query more data for deeper analytics from PureData. For example, you can query data in the PureData System together with:
- Data in IBM BigInsights or other Hadoop implementations
- Relational data stores (DB2, 3rd party and open source databases like Postgres, MySQL, etc.)
- Multi-generational PureData Systems for Analytics systems (“Twin Fin”, “Striper”, “Mako”)
The following is a summary of some new features in the release that all help to support your needs for insights across a range of data types and stores:
- Generic connector for access to structured data stores that support JDBC
This generic connector enables you to select the database of choice. Database servers and engines like Teradata, SQL Server, Informix, MemSQL and MAPR can now be tapped for insight. We’ve also provided a capability to handle any data type mismatches between differing source/target systems.
- Support for compressed read from Big SQL on IBM BigInsights
Now using the Big SQL capability in IBM BigInsights, you are able to read compressed data in Hadoop file systems such as Big Insights, Cloudera and Hortonworks. This adds increased flexibility and efficiency in storage, data protection and access.
- Ability to import databases to Hadoop and append to tables in Hadoop
New capabilities now enable you to import databases to Hadoop, as well as append data in existing tables in Hadoop. One use case for this is backing up historical data to a queryable archive to help manage capacity on the data warehouse. This may include incremental backups, for example from a specific date for speed and efficiency.
- Support for the lastest Hadoop distributions
Fluid Query v. 1.6 now supports the latest Hadoop distributions, including BigInsights 4.1, Hortonworks 2.5 and Cloudera 5.4.5. For Netezza software, support is now available for NPS 7.2.1 and INZA 3.2.1.
Fluid Query 1.6 can be easily downloaded from IBM Support Fix Central. I encourage you to refer to my “Getting Started” post that was written for Fluid Query 1.5 for additional tips and instructions. Note that this link is for existing PureData clients. Refer to the section below if you are not a current client.
Packaging and distribution
From a packaging perspective we refreshed IBM Netezza Platform Developer Software to this latest NPS 7.2.1 release to ensure the software suite is current from IBM’s Passport Advantage.
|Supported Appliances||Supported Software|
For the Netezza Developer Network we continue to expand the ability to easily pick up and work with non-warranted products for basic evaluation by refreshing the Netezza Emulator to NPS 7.2.1 with INZA 3.2.1. You will find a refresh of our non-warranted version of Fluid Query 1.6 and the complete set of Client Kits that support NPS 7.2.1.
Feel free to download and play with these as a prelude to PureData Systems for Analytics purchase or as a quick way to validate new software functionality with your application. We maintain our commitment to helping our partners working with our systems by maintaining the latest systems and software for you to access. Bring your application or solution and work to certify, qualify and validate them.
For more information, NPS 7.2.1 and INZA 3.2.1 software, refer to my post.
Doug has over 20 years combined technical & management experience in the software industry with emphasis in customer service and more recently product management.He is currently part of a highly motivated product management team that is both inspired by and passionate about the IBM PureData System for Analytics product portfolio.