Varada Wins ‘DataOps Platform of the Year’ in 2021 Data Breakthrough Awards
Read MoreThe complexity and extensive processing effort required to serve data-driven applications and APIs, in terms of time-to-value and cost, create a significant challenge in fully monetizing data assets. Existing solutions only optimize one aspect of the problem: either performance or business agility. Optimizing performance requires major data modelling and pre-aggregations which limit the ability to support application development velocity. Some solutions that support rapidly changing data requirements often deliver unacceptable SLAs due to ETL / processing delays, and a reliance on large data scans.
Varada’s data infrastructure platform indexes data on all of dimensions, at the structure and granularity of the source. Varada operates directly on top of existing sources of truth. Varada automatically synchronizes changes and indexes new data rapidly. Queries can be served to accommodate operational SLAs less than 60 seconds from data arrival. By eliminating and modeling, Varada enables any query to run while supporting various SLAs on response time, concurrency for users and analytics API calls, and data freshness.
Varada adaptively and fully indexes all dimensions of trillions of rows, supporting any standard SQL query.
Cut down on manual modeling to support fast time-to-value and ensure optimal query flexibility.
Deliver x100 faster query response time across any dimension, using the index to filter, join and aggregate data.
Deliver predictable and consistent SLA on response time and data freshness. Support different SLA tiers to optimize data monetization.
Define any operational dataset on any data source with a standard SQL command. Easily adjust the operational dataset to support high-velocity application development and various customer requirements.
Varada connects directly to a wide range of data sources, including the data lake (AWS S3, on-prem Hadoop, etc.), data catalogs (Hive Metastore, AWS Glue) and other sources (MySQL, PostgreSQL, etc.).
Keep data in your full control and in your own VPC, employ existing security policies.
Extend your Presto-based workflows to support low latency analytics with materialized indexed views.
