Real-Time ingest engine

Ingest Streaming Data to Your Lakehouse in Real Time

Ingest, transform, and query logs, security and clickstream events on your storage, with no extra pipelines, no silos. Built for enterprises that demand governance, scale, and faster event-to-insight, without lock-in.
Run Anywhere

<1 min

data freshness

60%

lower costs

zero

migration
Architectural diagram titled “Without e6data.” Click-stream, event, and log data enter an ETL/Flink box, then a destination table that can be Iceberg, Delta Lake, or other formats, hosted on any cloud; freshness is shown in minutes with multiple data pipelines in play.

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Architectural diagram titled “With e6data.” The same streams land in Kafka, pass through e6data’s real-time streaming ingest engine, write Parquet files, land in Iceberg tables, and work on any cloud; maintaining data freshness in seconds.

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Developer Experience

Ingest every log, click, and query instantly on your storage stack

Materialize Kafka topics to Iceberg tables in your S3, GCS or ADLS, and query them in under 60s at object-store cost, without any migration, and ETL.

Query Kafka topics as Iceberg tables

High-performance queries with exactly once delivery, ACID guarantees, dynamic scaling, and instant failure recovery.
Diagram of Kafka topics being materialized to Iceberg and Parquet, with “event-to-insight < 1 min,” and landing in user’s object storage (Amazon S3, GCS, ADLS).

Deploys in your object storage or lakehouse

Rely on one governed, unified source for every analytics workload with no migrations, no duplicates, and minimal ETL.
e6data’s compatibility with all platforms (Databricks, Snowflake, Microsoft Fabric, and more), object storage (AWS S3, GCS, ADLS)

Predictable and lower total compute costs

Avoid extra storage and indexing fees. Ingest and analyze billions of events natively in your lakehouse with custom retention.
Simple line chart: an exponential curve for “Number of Events (in billions)” rises faster than a linear cost line, showing costs grow slower than data volume with e6data’s real-time streaming ingest engine.

Unified data for LLM agents, ML pipelines

Build custom AI agents on unified, high-fidelity data from every source, be it streaming or historical, in any format.
Real-time ingest architecture: Clickstream data feeds use cases like log and user analytics, each streaming into LLMs, then to Agents—for agentic AI with unified data context.

Enterprise-grade security and governance

Row/column-level control, IAM integration, and audit-ready logs. SOC 2, ISO, HIPAA, and GDPR compliance, secure by design.
Sample table listing first name, last name, and masked SSNs, overlaid with compliance badges for ISO, GDPR, HIPAA, and SOC 2, displaying e6data’s compliance and data governance.
“We’ve been looking to move our logs to S3 since the costs became super high. With e6data, it became possible faster as our p95 & p99 latencies were maintained. All our logs now ingest & query in S3. ”
Head of Platform Engineering
B2B observability SaaS
Use Cases

Cut MTTR, catch threats and drive growth: insights in under a minute

Petabyte-scale streaming to Iceberg powers real-time dashboards and alerts without high compute costs, vendor lock-in, or data migration.

Log Observability

Full-fidelity logs in <1 minute for instant RCA—no sampling, no indexing fee. The query engine pushes materializes Kafka topics to Iceberg tables, so p95 search latency stays sub-minute even at billions of rows. Enables deterministic and timeline-accurate incident analysis.

Security Analytics

Auth events, VPC flows, DNS lookups, and EDR telemetry all land in a single Iceberg table, snapshotted continuously on low-cost object storage with custom retention. Each snapshot is instantly queryable, feeding live data for anomaly detection before threats escalate.

User Analytics

Mobile, web, and backend clickstreams—stream to Iceberg within seconds, so no event is dropped. Product teams can chart fresh cohorts, fire engagement triggers, and join behavioural data to other tables without ETL or exports, enabling AI/ML-driven personalization.

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.

FAQs

Do I need extra ETL pipelines to use e6data’s real-time ingest engine?
No extra pipelines; the engine streams, transforms and makes data queryable right on your storage.
Where can I deploy the real-time ingest engine?
Directly on S3, GCS, ADLS or any lakehouse/hybrid setup—wherever your data already lives.
Can I query data immediately after it lands?
Yes. Streams are query-ready in under 60 seconds with ACID and exactly-once guarantees.
Which workloads see the biggest gains with the real-time ingest engine?
Log observability, security analytics, and click-stream events, gain up to 10x faster and 60% lower TCO.
How reliable are scheduled analytics jobs on e6data?
They run with 99.99% reliability, even at high refresh frequencies.
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