Varada Data Virtualization Platform
Video II
Varada offers the new standard for data virtualization, with a smart indexing layer. Our ability to index big data delivers exceptional price and performance, so that agility and ease-of-use can be leveraged across a very wide range of use cases.
In this video (part II of III) you’ll learn how we do the magic and accelerate queries with our unique indexing technology. Varada indexes operational datasets as they are loaded, at the rate of the data ingest, without any user intervention or post-processing. The result is that any query on an inline indexed dataset will find an index ready for it.
The inline index is adaptive to the data so that each dimension (columns) is split into very small pieces, called nanoblocks.
To ensure fast performance for every query and each nanoblock, Varada leverages a variety of indexing algorithms and indexing parameters that adapt and evolve as data changes to ensure best fit index to any data nanoblock. Inline Indexing is used for:
- Filters – any SQL WHERE clause, on any column, within an SQL statement can use an index. Indexes are used for point lookups, range queries and string matching of data in nanoblocks
- Joins – any SQL JOIN statement uses the index of the key column; the index can be used for dimensional JOINs — combining a fact table with a filtered dimension table, for self-joins of fact tables based on time or any other dimension as an ID, and for a joins between materialized (indexed) data and virtualized data sources Varada will automatically detect and use the index for applicable JOINs
- Aggregations (coming soon) – SQL aggregations and grouping can leverage nanoblock indexes to accelerate performance
To learn more about Varada’s platform, go to video #1 that offers an overview of the platform as well as the various data sources Varada connects to, and video #3 that shows how Varada serves any SQL application, BI tools , etc.
