Best Relational Database for Apache Spark

SingleStore (formerly MemSQL) is a distributed, highly-scalable SQL database that can run anywhere. We deliver maximum performance for transactional and analytical workloads with familiar relational models. SingleStore is a scalable SQL database that ingests data continuously to perform operational analytics for the front lines of your business. Ingest millions of events per second with ACID transactions while simultaneously analyzing billions of rows of data in relational SQL, JSON, geospatial, and full-text search formats. SingleStore delivers ultimate data ingestion performance at scale and supports built in batch loading and real time data pipelines. SingleStore lets you achieve ultra fast query response across both live and historical data using familiar ANSI SQL. Perform ad hoc analysis with business intelligence tools, run machine learning algorithms for real-time scoring, perform geoanalytic queries in real time.

Serverless, interactive querying for analyzing data in IBM Cloud Object Storage. Query your data directly where it is stored, there's no ETL, no databases, and no infrastructure to manage. IBM Cloud SQL Query uses Apache Spark, an open-source, fast, extensible, in-memory data processing engine optimized for low latency and ad hoc analysis of data. No ETL or schema definition needed to enable SQL queries. Analyze data where it sits in IBM Cloud Object Storage using our query editor and REST API. Run as many queries as you need; with pay-per-query pricing, you pay only for the data scan. Compress or partition data to drive savings and performance. IBM Cloud SQL Query is highly available and executes queries using compute resources across multiple facilities. IBM Cloud SQL Query supports a variety of data formats such as CSV, JSON and Parquet, and allows for standard ANSI SQL.

Apache Phoenix enables OLTP and operational analytics in Hadoop for low-latency applications by combining the best of both worlds. The power of standard SQL and JDBC APIs with full ACID transaction capabilities and the flexibility of late-bound, schema-on-read capabilities from the NoSQL world by leveraging HBase as its backing store. Apache Phoenix is fully integrated with other Hadoop products such as Spark, Hive, Pig, Flume, and Map Reduce. Become the trusted data platform for OLTP and operational analytics for Hadoop through well-defined, industry-standard APIs. Apache Phoenix takes your SQL query, compiles it into a series of HBase scans, and orchestrates the running of those scans to produce regular JDBC result sets. Direct use of the HBase API, along with coprocessors and custom filters, results in performance on the order of milliseconds for small queries, or seconds for tens of millions of rows.