Zero Ops Data Streaming

Streamkap is the fastest way to build streaming applications
Power real-time AI & analytics with sub-second CDC & stream processing. Kafka & Flink without the headaches

Trusted by teams at

WHY STREAMKAP

Replace batch ETLwith streaming in minutes

Move data with <250ms latency using change data capture (CDC) for minimal impact on the source database and real-time updates.

Connect your data sources and move data to your target destinations with our automated, reliable and scalable data movement platform:

  • Dozens of pre-built, no-code source connectors
  • Automated schema drift handling, updates, data normalization and more
  • High performance change data capture for efficient and low impact data movement
Explore sources
CDC pipeline diagram

Streaming transformations power faster, cheaper, more rich data pipelines:

  • Python and SQL transformations
  • Common use cases include:
  • Hashing, masking, aggregations, joins, unnesting JSON and more!
Explore transformations
Data transformation diagram

Want to move to streaming event driven architecture but not ready to manage lower level systems like Apache Kafka and Flink?

  • Start with out of the box use cases like CDC
  • Expand to writing to or reading from Streamkap's Kafka without any of the headaches
  • Transform event data, merge with database data and more!
Explore Kafka
Event streaming diagram

As easy as Fivetran but 15x faster and 3x lower cost

Read how SpotOn saved 66% with us
Real-time streaming benefits illustration

Realtime

Sub-second latency

Data transformation diagram

3x Cheaper

Lower total cost of ownership

SET IT UP

The easiest way to stream data in real-time

Streamkap setup interface
1.

Connect Source

Authenticate your source database and choose the tables you want to sync

View sources
Connection flow line
2.

Connect Destination

Connect your destination account, Snowflake, Databricks, BigQuery and more with just a few clicks

View destinations
Data transformation diagram
3.

Create Pipeline

Connect your source and destination to get data moving with <250ms latency

Get started
Pipeline setup icon

Setup in minutes

All you need is your source and destination database credentials to get data moving

Automatic scaling icon

Automatic Scaling

Streamkap scales automatically to handle data at any scale with flexible retention

Monitoring and alerting icon

Monitoring and Alerting

Power your production workloads with confidence that your pipelines are healthy and you'll know if there is an issue

Flexible pricing icon

Flexible and Predictable Costs

Get started with flexible plans and lock-in predictability when you're ready

MySQL connector
MongoDB connector
Redis connector
PostgreSQL connector

INTEGRATIONS

CDC-Ready Connectors

Our source and destination database connectors are built for scale, reliability, and cost efficient real-time replication from PostgreSQL, MySQL, and MongoDB into BigQuery, Snowflake, Databricks and more.

Learn more about all connectors
Snowflake connector
BigQuery connector
Databricks connector
ClickHouse connector

TESTIMONIALS

Why our customers love Streamkap

Great technology and a great team

SpotOn logo

Streamkap was 4x faster and had 3x lower total cost of ownership than our previous solution

Marcin Migda

Staff Data Engineer

Read Case Study
Nala logo

Streamkap provides that speed at a cheaper cost, and combined with the other tools, we can build and raise the sophistication of the work that we can deliver. Without Streamkap, that was very difficult. That's really what it comes down to.

Dai Renshaw

Head of Data

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Fleetio logo

Streamkap is a big part of our stack now because these data products that we're releasing heavily rely on the data that Streamkap is producing to Snowflake. If there's ever any issues, Streamkap can recover itself. Compared to our old tool, if one small thing happened, it would just completely break. On top of that, the cost that we have in Snowflake now for loading data on Streamkap is like next to nothing.

John Michael Mizerany

Senior Software Engineer

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Niche logo

The old pipeline had a lot of overhead. Our old data pipeline was not running in near real-time and was very limited in scope. As I got to know the Streamkap platform, I decided — we should implement it, full steam ahead. From that set-up and configuration perspective, I don't even think we spent even a day. Then we did a cost-benefit analysis, and cost-wise, it was just a no-brainer to move to Streamkap.

Vikram Chauhan

Head of Data Engineering

Read Case Study
Koheisan logo

The migration to Streamkap has resulted in clear and predictable billing, reducing unexpected costs. Success metrics include a 54% reduction in data-related costs. GCP Datastream lacked reliable support channels for issue resolution, but Streamkap provides prompt assistance through Slack, making it easy to consult and resolve problems quickly.

Kohei Hasegawa

CTO

Drop-in Replacement for your Batch ETL

Start for free