Streaming to object storage is slow to query
Data lands, but only becomes useful hours later through a separate batch step.
USE CASE
Real-time ingest to object storage
Stream Kafka, CDC, and HTTP sources straight into open Iceberg tables on your object storage, queryable in ~15 seconds. No Flink pipeline to babysit, no separate ETL hop.
IN PRODUCTION
<1singest latency
~15sevent to queryable as Iceberg
$0per-GB indexing fees
PROBLEMS THIS SOLVES
The problems this solves
Pipelines sprawl
Separate ingest, transform and index systems multiply cost and failure points.
Indexing fees and format lock-in
Per-GB charges and proprietary stores tax every gigabyte you keep.
Streams in, open tables out
One engine ingests, transforms, and indexes as data lands, writing governed Iceberg to your own object storage. It replaces Flink-style pipelines and separate ETL hops.
RUNS WITH YOUR DATA STACK
No custom glue code needed
SOURCES
Kafka, CDC, and HTTP, with no shuffle.
TABLE FORMAT
Writes open Iceberg you fully own.
STORAGE
Your object storage, in your account.
CATALOG
Registers in any catalog you run.
QUERY
Read by any engine, not just ours.
Straight to open tables, no pipeline to run
Straight to open tables
Streams land as governed Iceberg you own, readable by any engine, not a proprietary index locked to one vendor.
proof: queryable in ~15s as open Iceberg
proof: sub-second ingest latency
No pipeline to babysit
Ingest, transform, and table maintenance run in one engine, replacing Flink-style pipelines and a separate ETL hop.
proof: sub-second ingest latency
proof: $0 per-GB indexing fees
Your storage, your bill
Data sits in your own object storage with no per-GB indexing fees, so keeping more history costs storage and nothing else.
proof: $0 per-GB indexing fees
RESULTS
One engine from stream to query
<1singest latencyEvents are durably captured within a second of arriving on object storage.
~15sto queryableFrom landing to queryable on open Iceberg in about fifteen seconds.
$0per-GB indexingNo per-gigabyte indexing fees, so retention is a value decision, not a cost one.
POWERED BY · INGEST & INDEX
This use case runs on e6data Ingest engine
A streaming ingest engine that lands Kafka, CDC, and HTTP sources in open Iceberg tables with sub-second latency, queryable in ~15 seconds, with no per-GB indexing fees.
Questions your team will ask
Plain answers for the evaluator in the room.
Does this replace my streaming pipelines?
It replaces Flink-style pipelines and a separate ETL hop for getting streams into the lakehouse. Ingest, transform, and table maintenance run in one engine that writes open Iceberg.
Who can query the tables it writes?
Anything that reads Iceberg: the e6data Query engine, Spark, Trino, Snowflake, or Databricks. The output is your table, in your catalog, under your governance.
Will it run in my environment?
Any cloud, your VPC, on-prem, hybrid, air-gapped, or sovereign. Streams never leave your perimeter, and data lands in your own object storage.
TALK TO US
Book a demo on your own workloads
Reach out to book a demo, share challenges you’re facing, and tell us how this fits into what you’re currently working on or thinking about.
Problems we’re solvingThanks.
An actual person replies, usually within one working day.