Lakehouse Compute Engine

Atomic architecture to reduce costs and improve performance at scale

Run high-concurrency, complex SQL analytics and AI workloads—directly within your lakehouse. For enterprises facing throttling, rationing, and vendor lock-in. Compatible with all table formats and catalogs.
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10x

faster

60%

lower costs

zero

data movement
Trusted by Data Teams at
‍“We achieved 1,000 QPS concurrencies with p95 SLAs of < 2s on near real-time data & complex queries. Other industry leaders couldn’t meet this even at a far higher TCO.”
Chief Operating Officer
“We’ve been impressed with e6data’s performance, concurrency, and granular scalability on our resource-intensive workloads.”

Head of Platform Engineering
Technology

Why is e6data 10x faster at 60% lower cost?

Because architecture matters. No more spinning up clusters or blindly throwing compute at every workload.
w/o e6data

Legacy Centralized, VM-centric architectures

Depend on a single coordinator node — creating bottlenecks, single points of failure, and expensive step-jump scaling. Even slight increases in workloads trigger large cost spikes and SLA misses.
w/ e6data

e6data's Decentralized, k8s native architecture

Scales granularly with stateless services, with scaling granularity down to 1 vCPU increments. Result: 10x faster queries, consistently met SLAs, and a predictable 60% lower TCO at petabyte-scale.
Benchmarks
Vs. legacy lakehouse engine

3.09x

Faster
TPC-DS
Delta
8 QPS
Vs. legacy QUERY engine

11.02x

Faster
TPC-DS
Fabric
30 cores
Query type: comparison

1.58x

Faster
TPC-DS
Delta
AWS
XS
Vs. legacy lakehouse engine

67.64%

Lower cost
TPC-DS
Delta
8QPS
Vs. legacy query engine

7.04x

Faster
TPC-DS
Iceberg
XS
Query type: logical

1.80x

Faster
TPC-DS
Delta
AWS
XS
Vs. legacy lakehouse engine

3.08x

Lower p99 latency
TPC-DS
Delta
8 QPS
e6data + Fabric

3081.2s

Execution time
TPCDS_1000
Delta
30 cores
e6data + Fabric

60.05%

Lower cost
TPC-DS
Fabric
30 cores
High Concurrency

1.20x

Faster
TPC-DS
Delta
AWS
XS
Vs. legacy lakehouse engine

3.09x

Faster
TPC-DS
Delta
8 QPS
Vs. legacy QUERY engine

11.02x

Faster
TPC-DS
Fabric
30 cores
Query type: comparison

1.58x

Faster
TPC-DS
Delta
AWS
XS
Vs. legacy lakehouse engine

67.64%

Lower cost
TPC-DS
Delta
8QPS
Vs. legacy query engine

7.04x

Faster
TPC-DS
Iceberg
XS
Query type: logical

1.80x

Faster
TPC-DS
Delta
AWS
XS
Vs. legacy lakehouse engine

3.08x

Lower p99 latency
TPC-DS
Delta
8 QPS
e6data + Fabric

3081.2s

Execution time
TPCDS_1000
Delta
30 cores
e6data + Fabric

60.05%

Lower cost
TPC-DS
Fabric
30 cores
High Concurrency

1.20x

Faster
TPC-DS
Delta
AWS
XS
Learn more in docs
Explore Benchmarks
Use Cases

Run your most resource-intensive SQL and AI workloads

Get predictable SLAs, instant query responses, and radically lower compute costs—all with no query rewrites or app changes.

Packaged Analytics

Deliver embedded, multi-tenant analytics seamlessly within your SaaS applications. Gain 10x faster performance at scale while reducing infrastructure costs by up to 60% and operational complexity.

Interactive Analytics

Enable real-time dashboards and dynamic data exploration at massive scale. Deliver sub-2-second response times for 1000+ QPS with consistent SLAs and UX and without any latency.

Ad-hoc Analytics

Run complex ad-hoc queries 10x faster across diverse data sources (object storage, OLAP, data streams, and more) from a unified engine. Achieve zero-failed SLAs due to poorly optimized queries and resource constraints.

Scheduled Analytics

Run frequent, high-volume scheduled analytics with 99.99% reliability for scheduled workflows—without downtime, data delays, or compute cost overruns, even with rapid refresh cycles.


Real Time Ingest

Stream data into your lakehouse with sub-second latency. Skip Flink, ETL, and pipeline overhead. Query fresh events instantly using SQL or Python—no shuffle, no joins, no delay between ingestion and analysis.

Vector Search

Run semantic search on unstructured data using built-in cosine similarity. No vector DBs, no retrieval pipelines. Query text like structured rows with SQL—fast, scalable, and lakehouse-native for instant, AI-powered insights.

Packaged Analytics

Deliver embedded, multi-tenant analytics seamlessly within your SaaS applications. Gain 10x faster performance at scale while reducing infrastructure costs by up to 60% and operational complexity.

Interactive Analytics

Enable real-time dashboards and dynamic data exploration at massive scale. Deliver sub-2-second response times for 1000+ QPS with consistent SLAs and UX and without any latency.

Ad-hoc Analytics

Run complex ad-hoc queries 10x faster across diverse data sources (object storage, OLAP, data streams, and more) from a unified engine. Achieve zero-failed SLAs due to poorly optimized queries and resource constraints.

Scheduled Analytics

Run frequent, high-volume scheduled analytics with 99.99% reliability for scheduled workflows—without downtime, data delays, or compute cost overruns, even with rapid refresh cycles.


Real Time Ingest

Stream data into your lakehouse with sub-second latency. Skip Flink, ETL, and pipeline overhead. Query fresh events instantly using SQL or Python—no shuffle, no joins, no delay between ingestion and analysis.

Vector Search

Run semantic search on unstructured data using built-in cosine similarity. No vector DBs, no retrieval pipelines. Query text like structured rows with SQL—fast, scalable, and lakehouse-native for instant, AI-powered insights.
Developer Experience

Query everything, scale and secure fast on your own stack

Run SQL + AI workloads that auto scale, block bad jobs, run vector search, and stay secure with row/column masking—no tuning, no trust issues.

Runs with your data stack

Supports all lakehouses, table formats, catalogs, BI tools, and RAG apps—no custom glue code needed.
View All Integrations
Lakehouse
Queries directly with zero data movement.
Application
Connects to any BI tool, RAG app, chatbot, of choice.
Table Formats
Highly performant on all table formats.
Catalogs
No disruption to your governance. Fully compliant.

SQL meets AI, right in your lakehouse

Query structured and unstructured data with cosine similarity. No vector DBs. Just pure vector search.

Auto-scaling that adapts to query load

Set min and max, we handle the rest. Executors scale with load with no latency spikes, no job failures, no manual tuning.

Guardrails to stop “bad” queries early

Set thresholds per cluster. Log, alert, or cancel in real time before bad queries waste compute.

Sub-second streaming of data in your lake

Stream directly to your lakehouse, query with sub-second latency- query with SQL/Python. No Flink, no ETL, no learning curve.

Enterprise-grade security and governance

Row/column-level control, IAM integration, and audit-ready logs. SOC 2, ISO, HIPAA, and GDPR—secure by design, with no slowdown.
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