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Upsolver Lookup Tables

The First Indexing Engine for Data Lakes


Query Amazon S3 by any set of keys at high-throughput and milliseconds-latency using a REST API, without the overhead of managing any additional data stores.


10-15x

more data in memory compared to NoSQL databases

50k

reads per second, per server, at 1ms latency on average

100x

Faster time to production for real-time analytics and machine learning

"Upsolver saved 24 months of engineering that we would have needed to invest to see the same results with Redis or DynamoDB."

Amit Attias, CTO, Bigabid

What are Upsolver Lookup Tables?

Lookup Tables add indexing at high cardinality and performance to your data lake. They enable users to index data by a set of keys and then retrieve the results in milliseconds. Unlike NoSQL alternatives, Upsolver's ETL platform stores indexed data on S3 rather than local servers, which turns IT-intensive cluster management into a non-issue. Lookup Tables leverage break-through compression technology and smart rollups that enable 10X-15X more data in-memory compared to alternatives.


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Key Benefits and Feature Highlights

Reduce 70-90% of infrastructure costs by storing more data in RAM

Decoupled compute and storage for easy healing, scaling, and disaster recovery

Easy to create without ETL coding or IT management using a self-service UI and UpSQL

Query by any set of keys or time range.

Lookup Tables are stored on S3 as a time-series. Using smart rollups, Upsolver makes it possible to query any time range by any set of keys.



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Query S3 by any time window
Upsolver built-in data transformations

Rich library of out-of-the-box window aggregations

Capture real-time behaviour for users and devices, using window aggregations, nested aggregations and time-series aggregations.



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Simple REST API

Embed granular user or device data in your applications using a simple REST API and avoid the overhead of additional data stores.



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Upsolver API call example


Use Cases

Embedded Analytics

Serve data in sub-second latency to power real-time dashboards and data-driven apps

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Machine Learning ETL

Improve machine learning models and performance by adding user or device-level behavioral features

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Stateful ETL for Stream Data

Perform joins between multiple streaming sources or big tables with a high number of keys.

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GDPR and PII Removal

Enforce GDPR and other regulatory compliance by keeping track of all user records in your lake

Let's get personal: See Upsolver on your data in a live demo.

Schedule a free, no-strings-attached demo to discover how Upsolver can radically simplify data lake ETL in your organization.

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