Rockset, the serverless search and analytics company, is releasing a cloud service that allows developers and data scientists to put complex data sets to use in minutes instead of weeks.
“Modern data sets are messy and unstructured. Traditional data management systems force teams to spend more than 50 percent of their time just preparing and loading these data sets,” said Venkat Venkataramani, co-founder and CEO of Rockset. “What's the point of collecting new data if you cannot use it immediately and iterate quickly? Rockset has reimagined the stack in a new developer-friendly way, with fast SQL on raw data -- so you can go from data to applications in a few minutes.”
Rockset’s serverless data backend that continuously ingests raw data as it is generated and delivers real-time SQL queries at scale.
Its patent-pending Converged Indexing, which combines an inverted index, columnar index and document index, is optimized for key-value, time-series, document, search, aggregation and graph type queries out of the box.
It is backed by RocksDB, which combined with its Cloud Native Distributed Query Engine, delivers the performance and scale necessary for real-time operational applications and interactive data science.
Features include:
- Continuous schema-less ingest from data lakes, databases and streams including Apache Kafka, Amazon Kinesis, Amazon DynamoDB, Amazon S3 and Google Cloud Storage
- Smart schemas for JSON, XML, CSV, Parquet, Excel and PDF
- SQL, including JOINs, with 1,000+ QPS
- SDKs for Java, Python, Node.js, Golang and REST API
- Delivered as-a-service with self-serve access
Rockset empowers teams to serve data-intensive applications using a wide range of data formats from multiple sources, without having to model schemas or manage fragile extract-transform-load (ETL) pipelines.
For more information about this release, visit www.rockset.com.