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DATABRICKS PLATFORM COMPATIBILITY
Making your Databricks Data Platform Better:
New Capabilities. Extended Reach. Amplified ROl.
Keep what you love about Databricks—add e6data where it matters. Save $1.5M–$10M (60% TCO), get 10x more queries, unlock real-time capabilities in Databricks lakehouse, extend governance to multi-region & cloud, hybrid—all SQL & Iceberg compatible.
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Single compute engine handling all SQL and AI workloads
Databrick’s all-in-one engine makes it simple to ingest, transform, and query data from a single platform. Yet when workloads evolve, users demand higher concurrency support, stricter SLAs, Iceberg adoption, new capabilities, and justified costs—needs a single cluster can’t always meet.
e6data’s distributed k8s-native engine — built on atomic architecture
Keep what you love about Databricks—add e6data’s engine into bottleneck workloads. Each workload (ingest, ETL, query, AI) —scale instantly, save $1.5M-10M (≤60 % TCO), run 10x more queries, get real-time streaming, extend catalog & governance securely to multi-cloud—no data movement or SQL rewrites.
USE CASES
Query · ETL · Real-Time Ingest
Add e6data to solve pressing pain points while staying on your Databricks platform—no migration, no query changes, no governance changes.
Dashboards that scale up to 1000 QPS
Power real-time dashboards with sub-2-second response times at high concurrency with consistent SLAs.
SQL meet AI in your Databricks Lakehouse
Run semantic search on unstructured data using built-in cosine similarity in SQL. No vector DBs, no retrieval pipelines.
Multi-region, Multi-cloud, Hybrid made easy
The industry’s only Affinity and Locality-Aware Computing: 10x faster latency, 99% lower egress, 60% lower TCO.
Adopt Apache Iceberg, alongside Delta Tables
Query Iceberg on your Databricks lakehouse using our native-Iceberg support, extended across all table formats.
Stream and query your events data in Databricks lakehouse within seconds
Stream directly to your lakehouse, query with sub-second latency- query with your SQL dialect or Python. No Apache Flink, no ETL, no operational overhead.
Performance at production scale: run e6data in Databricks platform
Benchmarks
Up to 10x faster querying, sub-second p99 latencies
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Estimate your monthly cost
Up to 60% lower costs, granular, per vCPU scaling
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Deploy across multi-cloud, multi-region, and on-prem
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FAQs
How does e6data speed up Databricks and cut DBU costs?
e6data is powered by the industry’s only atomic architecture. Rather than scaling in step jumps (L x 1 -> L x 2), e6data scales atomically, by as little as 1 vCPU. In production with widely varying loads, this translates to >60% TCO savings.
I use both Snowflake and Databricks. Can I adopt e6data alongside both of them? Do I have to move out?
We integrate with your existing data architecture—whether you’re using Databricks, Snowflake, Trino, Athena, or any other engine—alongside your chosen catalog, governance framework, table format, and BI tools. You can deploy us anywhere: single or multi-cloud, multi-region, on-premises, or in a hybrid environment.
Can I query Iceberg and Delta Lake tables together?
Yes. Also, depending on your workload, you can see anywhere up to 10x faster speeds through our native and advanced Iceberg support.
Which workloads will gain the most from e6data?
We deliver performance gains and cost efficiency across all SQL and AI workloads, but our customers see even greater benefits under high-concurrency, complex workloads—especially those with high-cardinality joins, stringent SLAs, massive data scan volumes, and tight freshness requirements.
How is e6data licensed and how does it show up on my Databricks bill?
e6data is priced per usage of cores and is invoiced directly by e6data, separate from your Databricks DBU charges.
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Available at
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