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DirectoryData & AnalyticsStreaming & Real-Time AnalyticsDecodable

Decodable

About Decodable

Decodable provides a platform for real-time ETL/ELT and stream processing. The platform is fully managed and serverless for data movement and processing. It is built on Apache Flink and Debezium along with other integrated components. Pipelines can be built using SQL, Java, or Python. The platform includes built-in security and compliance features such as HIPAA, GDPR, and SOC 2. Decodable was launched in 2019.

Products

  • Fully Managed: A fully-managed, serverless platform for data movement and processing.
  • Simplified Development: Allows building real-time pipelines using SQL, Java, and Python with built-in connectors and CDC.

Used for

  • Streaming real-time data into vector databases for semantic retrieval in AI applications.
  • Performing ELT, ETL, and reverse ETL from a single platform.
  • Delivering data to power analytics, monitoring, and AI-driven decision-making.
  • Processing data between Kafka topics to curate data for other teams.
  • Connecting streaming data directly into Snowflake.

Who it is for

  • Application developers.
  • Data engineers.
  • Data scientists.

From Decodable's own website, read 2026-10-23. How we build listings.

How to evaluate Streaming & Real-Time Analytics

This is how the CIOPages Research Team evaluates this category. It is not an assessment of Decodable. It comes from our Streaming Data & Event Processing buyer guide.

25%
Throughput, Latency & Durability
Sustained throughput and tail latency at your partition count, ordering and exactly-once / at-least-once delivery guarantees, replication and multi-AZ durability, retention limits, and behavior under broker failure and rebalancing
20%
Operating Model & Architecture
Self-managed vs. fully managed vs. serverless vs. bring-your-own-cloud, KRaft (post-ZooKeeper) operations, diskless / object-storage-backed options, autoscaling, partition rebalancing, and upgrade and patching burden on your team
20%
Kafka-API Compatibility & Portability
Fidelity of the Kafka protocol (consumer groups, transactions, compaction), reuse of existing clients, connectors and tooling, lock-in to a single cloud, and the realistic effort to migrate in or out
15%
Stream Processing & Ecosystem
Native or integrated processing (Flink, Kafka Streams, Spark Structured Streaming, ksqlDB), connector catalog (CDC, sinks, sources), schema registry and governance, and direct landing into Iceberg / Delta lakehouse tables
10%
Security, Governance & Compliance
Encryption in transit and at rest, mTLS / SASL / OAuth and RBAC, audit logging, private networking, data residency and BYOC data-boundary control, and SOC 2 / ISO 27001 / GDPR coverage
10%
Cost Model & Economics at Scale
Pricing unit (capacity / throughput / consumption), inter-AZ and egress charges, storage and retention cost, processing billed separately, and how the bill behaves as volume, partitions, and connectors grow

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Quick Facts

www.decodable.co Pricing page
CategoryData & Analytics
SubcategoryStreaming & Real-Time Analytics
DeploymentFully-hosted, Bring Your Own Cloud (BYOC)
PricingUsage-based (credits consumed per task per hour)

We publish a detail only when we can point at the page it came from. Know when Decodable was founded or where it is based? Send it to us, free.

Keep reading

Buyer Guide
Real-Time Analytics Databases
Job 06
Secure and comply

AI agents act on systems with their own identities, and auditors and boards ask about them.

Job 05
Modernize the estate

AI agents need clean data and systems they can call, and old systems block both.