Sparkline SNAP

Sparkline SNAP: An Integrated OLAP platform on Spark

Sparkline SNAP platform is a modern B.I platform geared for analysis on very large datasets across SQL and non-SQL workloads. The SNAP platform is designed to

  1. Accelerate: Think time response for queries ( SQL and more) on Hadoop/S3 datasets. Eliminate joins and ETL and avoid complex extracts and still get fast query performance.
  2. Automate : Full management of data and indexes to eliminate manual extracts and management for ad-hoc analysis.
  3. Adapt : Most products are built with static optimization. Organization grow and analysis need changes with new queries, new data and new use cases. SNAP adapts on the fly by “learning” what questions are asked and continuously optimizes for performance.

SNAP Indexes

SNAPs are indexes on your structured data. An in-memory OLAP Index is the fastest way for analyzing billions of rows of multi-dimensional data. The SNAP OLAP Index is the first type of index from SparklineData, designed to provide lightning fast response times for business OLAP/B.I queries as well as machine learning and AI workloads on Spark.


AMP is our core engine on Spark that optimizes and translates queries to utilize SNAPs for ultra fast results. It runs as a native Spark application and is designed to handle high concurrency queries on large multi-dimensional datasets.

SNAP Cubes

SNAP cubes provide business level abstractions to define dimensions, measures and hierarchies. Cubes provide a logical abstraction to a star schema at the lowest granularity. Unlike OLAP cubes, SNAP cubes don’t need pre-aggregation or summarization avoiding expensive and complex summary table builds.

Watch demo videos

See videos on querying 100 million row datasets on Tableau and Zeppelin

Learn more about SNAP

Access our documentation and contact us to experience SNAP on your own dataset