Real-Time Upserts

Scale up, costs down

StarTree performs upserts at ingest for millions of rows per second while reducing infrastructure costs.

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StarTree performs upserts at ingest, making it incredibly efficient, fast, and scalable

Lowest Price

Reduce costs by minimizing compute and memory intensive operations

Freshest Data

Increase data freshness by removing a step

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Massive scalability through minimizing processing overhead

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Amberdata: Real-Time Analytics for the Entire Cryptoeconomy

Results

reduced infrastructure costs
66%
insert events per second
350k
query latencies
Sub-second

Uses Cases

Financial Analysis
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The challenge with upserts

An upsert is a database operation that combines update and insert functions into a single operation, offering improved insight accuracy, enhanced data freshness and simplified architecture.

Upserts, while simple in operational databases, can pose challenges in analytical databases by disrupting efficient bulk-loading, conflicting with columnar storage, and degrading query performance due to re-indexing.

overview

What makes StarTree upserts unique

StarTree upserts

Ingestion-time reconciliation

StarTree revolutionizes upserts with ingestion-time reconciliation. It appends new records, uses metadata for status, marks obsolete records, and balances storage between memory and external systems. This approach improves scalability and reduces memory overhead.

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Traditional upserts

Pre-ingestion reconciliation

Many vendors attempt to determine if a record is an insert or an update before data enters the database. This method increases data pipeline complexity and memory usage. It requires large volumes of temporary data, slows ingestion, and leads to ballooning overhead as data volumes grow

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Traditional upserts

Query run-time ingestion

Query-time reconciliation works for low-volume scenarios but becomes costly and inefficient as queries increase. It adds processing time, requires extra resources, and impairs real-time analytics performance

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Ready for real-time?

StarTree Cloud customers experience over 50% infrastructure cost savings. Book a demo to learn how your organization can get started.

Real-world benefits of real-time upserts from StarTree customers
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“The benefits of migrating to StarTree and Pinot center around three areas: query performance, SLAs, and cost. With Pinot, we are now in the subseconds to milliseconds range, the higher query concurrency means we can serve more customers faster, and we’ve been able to reduce our infrastructure costs.”

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Joanes Espanol
CTO and Co-Founder
features

Perform upserts for millions of rows per second

Achieve real-time data insights with scalable, efficient storage.

Deletes

Remove obsolete data from your database that you don’t want to see in future queries. Once our real-time engine encounters a record with a delete column, the primary key will no longer be part of queryable documents — saving you headaches.

Deletes Upserts

Partial upserts

Update some of the fields in a record, but not all of them. Partial upserts enable flexible handling of data streams with partial information — perfect for Change Data Capture (CDC) streams where only updated columns are received.

Partial Upserts

Compaction

Minimize disk space and overall infrastructure costs by periodically replacing obsolete records in your database with newer compacted segments that only contain valid records.

Compaction Upserts

Configurable comparison column

Select a different time column for resolving upserts, rather than using the default. Perfect for when you need to prioritize records based on a different timestamp — not the most up-to-date record.

Comparison Upserts

Bootstrap and backfill

Efficiently bootstrap (initialize) and backfill (update past data) into an upsert-enabled table, using a batch data pipeline to directly upload segments.

Bootstrap Upserts

Ready to deploy real-time analytics?

Start for free or book a demo with our team.