Db2: A Classic Database Not Suited for Modern Apps
IBM DB2® has been an important part of the enterprise IT infrastructure since the 90s for high availability and operational use cases. DB2 was originally built on mainframe technology and is now available on many platforms. However, legacy SQL databases such as DB2 do not have the ability to scale automatically across multiple nodes.
Cloud Migration Considerations
If you have an application powered by Db2 and you plan to migrate to the cloud you may be considering a few different options:
- Migrate the application and Db2 to the cloud
- Migrate the application to a cloud native RDBMS
- Rewrite the application on a cloud native NoSQL platform.
We believe that none of these options are cost effective nor do they provide a foundation to extend the application with new data and AI. Here’s why:
| Approach | Cost Impact | Modernization Limitation |
| Migrate Both App and Db2 | Db2 is too expensive | Can’t scale out |
| Migrate to cloud RDBMS | Cloud RDBMS can’t provide analytics and need to be coupled with cloud data warehouses increasing database costs | ETL limits real-time capabilities and no native ML |
| Rewrite to NoSQL | Super expensive to re-write application because not only do you have to rewrite all the data access you have to write primitives that SQL has and NoSQL does not. | NoSQL systems can not handle analytics |
In-Database Machine Learning
ML MANAGER: KEY BENEFITS
Support for Jupyter Notebooks: In Splice Machine 3.0 Jupyter notebooks are the standard. Splice Machine’s native Jupyter support comes with JupyterHub as well as BeakerX
Industry-Leading Libraries (Coming Soon): Access to the H2O Libraries, including deep learning TensorFlow integration, GLM, GBM, XGBoost, and AutoML
Ease of Use Across the Entire Product: Access to Apache Spark’s ML library, including algorithms, featurization, pipelines, persistence and utilities
Rapid Experimentation: MLflow to manage the experiments and model runs based on key parameters, versions and metrics
Seamless Deployment: MLflow packages models into Docker images, which are then deployable directly via Sagemaker for implementation
Superior Performance: Direct API between Splice Machine tables and Spark Data Frames for high performance
Take a look at ML Manager in this quick demo hosted by Ben Epstein, Machine Learning Engineer for Splice Machine, and click the button to access a full video demo.
Splice Machine: A Proven Replacement for Db2 that Delivers Lower Costs, Scale Out and Intelligence
Splice Machine is a scalable SQL database that enables companies to modernize their legacy and custom applications to be agile, data-rich, and intelligent – all without re-writes. Splice Machine not only reduces database licensing costs but also enables the applications to add new data sources at a massive scale. Splice Machine enables enterprises to unify analytics and machine learning that used to be on separate platforms to be native to the application thereby reducing ETL latency and infrastructure costs.
Why Splice Machine Is Best for Powering Db2 Applications
With Splice Machine, there is an opportunity to leapfrog the legacy database and modernize the application on a scale-out, HTAP database that has native AI and in-database machine learning. Splice Machine 3.0 now supports many Db2-specific extensions that make it easy to migrate from Db2 with minimal SQL rewrite. Examples include support for Db2 trigger syntax, error codes, text manipulation syntax, etc.
Customer Example: Global Payments Processor
- For a global payments processing company, Splice Machine migrated the existing SQL dispute resolution application from Db2 to Splice platform enabling millisecond queries on petabytes of payment history and live, up to the second streaming data.
- Splice Machine’s platform resulted in vastly improved customer service and a new system that can scale out to meet future business needs.
Customer Example: Leading Insurance Company
- A leading insurance company migrated its global claim, client, & policy applications from an on-premise Db2 environment to the Splice Machine platform in the Cloud. On Db2, it took too long to open up a new operating entity due to data center build-outs and the company was not able to use AI/ML models in real-time application.
- With Splice Machine, the insurance company will be able to expand into new geographical markets in record time without cloud vendor-lock-in and will be able to take intelligent predictive actions to lower fraud, AML, and litigation.