Streamkap Blog

How Streamkap handles CDC at scale across multi-tenant databases with thousands of schemas, delivering sub-second latency without managing Kafka or Flink.

How Limble solved data architecture complexity, maintenance overhead, and lowered costs.

How a Brazilian ATS leader InHire solved a data crisis in three weeks and built a cutting-edge, real-time AI platform without a single data engineer.

Snowflake streaming is now cheaper than batch-1-second latency at 10x lower cost. Learn how Streamkap achieves 75% cost reduction.

Kappa Architecture unifies streaming into a single model, eliminating Lambda's dual-layer complexity. Learn the key differences.

Stream MongoDB to Iceberg on S3 for e-commerce analytics. Enable real-time discounts and dynamic inventory with minimal latency.

Stream SQL Server to Iceberg on S3 for AI/ML workflows. Leverage time-travel queries and optimized performance without complexity.

Real-time lakehouse, simplified with Apache Iceberg and Streamkap

Apache Iceberg brings SQL tables to cloud storage with ACID transactions and time travel. Learn why it's essential for 2025.

Stream MySQL to Iceberg on S3 for real-time lakehouse analytics. Build scalable foundations with ACID transactions and schema evolution.

Stream PostgreSQL to Iceberg on S3 in minutes. Build data lake architectures for predictive maintenance and equipment monitoring.

At SpotOn, we had an existing pipeline that synchronized data from our production MongoDB to Snowflake. During peak demand, our customers require data to be as close to real-time as possible. To improve our latency (and reduce the cost of our maintenance and infrastructure), we started to look for a

Responsive connectors, no replication lag or stuck offsets in low activity tables.

Apache Iceberg adds ACID transactions and time travel to data lakes. Learn how Netflix uses it at petabyte scale for analytics.

As demand for real-time data insights grows, organizations need tools that can quickly move data from production applications into their data platforms.

Modern data teams often face the challenge of making operational data from systems like AWS-hosted MySQL available in analytics platforms like Databricks with minimal delay.

Data-driven decision-making is only as effective as the systems that power it. Unfortunately, many traditional architectures can't keep pace with today’s e-commerce velocity.

Modern data teams often face the challenge of making operational data from systems like AWS-hosted MySQL available in analytics platforms like Google BigQuery with minimal delay.

Modern data practitioners face an increasingly complex challenge: ingesting data from diverse sources into multiple destinations at high velocity. As NoSQL databases have surged in popularity, teams struggle with fast, reliable data movement from these operational stores to analytics platforms.

Stream MySQL data to MotherDuck for real-time analytics. Replace slow batch ETL with CDC streaming for faster financial analysis and market decisions.

In today’s fast-paced business environment, having access to accurate data at the right moment is crucial for making informed decisions.

Modern data teams often face the challenge of making operational data from systems like AWS-hosted SQLServer available in analytics platforms like Databricks with minimal delay.

In a World Where Speed is King, Don’t Let Your Data Fall Behind When decisions can’t wait, neither should your data. Outdated processes are slowing you down—but they don’t have to anymore.

Why LLMs fail at business data questions - your data warehouse doesn't speak business language. Semantic layers might be the key.

In today’s fast-moving world, businesses need the right data at the right time to make smart decisions. But let’s face it—traditional data processing can be slow and complicated.

AI startups claim massive ARR numbers, but many don't hold up to scrutiny. $10M claimed versus $3M actual is an 11x gap.

It's a Tuesday morning in London. You're rushing to catch the Tube when your phone buzzes. Your cousin in Lagos, Nigeria, needs money for emergency surgery, or the hospital won't admit her. You need to be able to send the money now and trust it will get there without any problems.

In today’s fast-paced business world, speed isn’t just an advantage—it’s a necessity. Decisions need to be made in real-time, but let’s face it: traditional data processing is clunky, slow, and overly complicated.

Chegg's stock plunged 89% due to AI disruption. Now MCP threatens Zapier's 8,000+ integrations - will they adapt or decline?

In an era demanding instant insights, your data can’t afford lag.When milliseconds determine outcomes, delayed data becomes a liability. Legacy systems throttle progress, but transformation is within reach.

The ZIRP era is over - data teams must now prove their value through real outcomes, not debates about definitions.

In today's ever-changing business climate, immediate access to reliable data is crucial for making sound decisions. However, traditional data processing methods are often too lengthy and slow to meet modern demands.

In today’s fast-paced business environment, having access to accurate data at the right moment is crucial for making informed decisions.

Change Data Capture refers to the process of capturing changes made to data in a source system such as a database, so that these change events can be used in the destination system, such as a data warehouse, data lake, data app, machine learning models, indexes, or caches.

Compare Streamkap and Airbyte for data integration. Understand the trade-offs between managed real-time CDC and open-source batch ETL to choose the right platform.

Compare Streamkap and AWS Database Migration Service for CDC and data replication. Understand latency, features, and when to choose each platform.

Compare Streamkap and Confluent for real-time CDC. Understand when you need a full Kafka platform vs a focused CDC solution for data warehouses and lakes.

Compare Streamkap's managed CDC platform with self-hosted Debezium. Same proven technology, dramatically different operational experience.

Compare Streamkap and Estuary for real-time data integration and CDC. Understand features, pricing, and architecture differences to choose the right platform.

An in-depth comparison of Streamkap and Fivetran for CDC and data integration. Compare pricing, latency, features, and use cases to choose the right platform.

AWS RDS PostgreSQL stands out as one of the most widely used production databases. Its global adoption and everyday usage have prompted Amazon to make it exceptionally user-friendly. New users can set up an RDS PostgreSQL instance from scratch in just a few minutes.

Getting started with Databricks is a breeze, regardless of your experience level. This guide provides clear instructions on how to create a new account or use your existing credentials, ensuring a smooth and efficient streaming process.

In today’s fast-moving world, businesses need the right data at the right time to make smart decisions. But let’s face it—traditional data processing can be slow and complicated.

To connect Streamkap to AWS RDS PostgreSQL, we need to ensure the database is configured to accept traffic from Streamkap by safelisting Streamkap’s IP addresses in the PostgreSQL instance.

Learn how Change Data Capture enables real-time data synchronization between your databases and data warehouses.

Let’s explore why Streamkap is a superior alternative to vanilla Kafka and compare it with other alternatives.

With Snowpipe Streaming, Streamkap can provide cost-effective real-time streaming connectivity and performance at a fraction of the competition’s cost — interoperable and Snowflake-ready.

Let’s look at the advantages of DynamoDB ETL and Rockset migration with Streamkap.

Streamkap helped Niche.com reduce their data latency by 95%, slash their data infrastructure costs, and transition from moving limited data to their entire set in less than a day of implementation.

Streamkap, a real-time data streaming provider, announced it has raised $3.3 million in seed and pre-seed funding for its low-cost, low-maintenance streaming ETL platform.

Streamkap is the Fivetran alternative for streaming

Find out how Streamkap enabled a leading fleet management software company to make the switch from batch processing to real-time streaming data.

As one of the fastest-growing software and payment companies, SpotOn needed a better way to scale their data batch-processing.

This hands-on guide is for data teams who wish to ingest data from MongoDB to a Snowflake data warehouse with sub-second latency and cost savings to boot.

This hands-on guide is for data teams who wish to ingest data from MySQL to a Snowflake data warehouse with sub-second latency and save on ETL costs.

This hands-on guide is for data teams who wish to ingest data from PostgreSQL to a Snowflake data warehouse with sub-second latency and sub-budget costs.

We’re excited to announce our new ClickHouse database connector for streaming CDC (Change Data Capture) data into ClickHouse.

How to use Snowpipe Streaming to stream Change Data Capture (CDC) to Snowflake

There is a big movement underway in the migration from batch ETL to real-time streaming ETL but what does that mean? How do these methods compare? While real-time data streaming has many advantages over batch processing, it is not always the right choice depending on the use case so let's take a loo

How to stream data into BigQuery