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Start here for the decision-making essentials: what Decodable does, who it is for, how it is accessed, and the first-party sources behind this profile.
Free tier available to start
scale as needed
Decodable is a fully-managed, serverless, cloud-native stream processing platform built on Apache Flink and Debezium. It enables pipelines in SQL, Java, or Python with built-in connectors and CDC, offering SOC 2 Type II, HIPAA, and GDPR compliance.
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Short answers to the questions buyers and builders commonly ask about Decodable. Each answer cites the shared ledger below, where every source is listed once.
Real-time stream processing with built-in connectors and CDC · Cloud-native stream processing platform powered by Apache Flink and Debezium · Single platform spanning simple data movement to advanced stream processing · Process data between Kafka topics (transform formats, route, cleanse, mask, filter, aggreg
Build pipelines using SQL, Java, Python and reliably move data with our built-in connectors, CDC, and powerful stream processing.
Data architects, engineers, and decision-makers evaluating real-time data platforms · Application developers, data engineers, and data scientists
tailored for data architects, engineers, and decision-makers evaluating real-time data platforms
Real-time applications including security and fraud detection, logistics, commerce, and so · Real-time scenarios including user behavior analytics, fraud detection, and AI feature sto · Process event and change data capture data using SQL · Multi-stream stateful joins and complex event processing
Modern applications work in real-time, from security and fraud detection, to logistics, to commerce and social.
Developer and Team plans include a limited number of concurrent real-time previews; Enterp
The Developer and Team plans include a limited number of concurrent real-time previews while the Enterprise plan includes an unlimited number of previews.
Free tier available to start; scale as needed
Start free and scale as you need.
Supports SQL, Java, Python, and dbt integration · Snowflake via pre-integrated Snowpipe Streaming API connector · Open source dbt-Decodable adapter to manage streaming and batch transformations in dbt · Apache Pinot real-time tables for streaming ingestion
Simplify development with support for SQL, Java, Python, and dbt integration.
This profile connects the jobs Decodable is described as handling with its delivery model, access options and the subjects used to match it to related products in this directory.
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Decodable
Real-time stream processing with built-in connectors and CDC · Fully-managed, serverless platform for data movement and processing · Bring Your Own Cloud (BYOC) account option available
Real-time stream processing with built-in connectors and CDC
Fully-managed, serverless platform for data movement and processing
Bring Your Own Cloud (BYOC) account option available
Built on an open core of Apache Flink and Debezium
Data architects, engineers, and decision-makers evaluating real-time data platforms
Audited and compliant with SOC 2 Type II, HIPAA, and GDPR per AT-C 315
Independent third-party penetration test performed at least annually
All services hosted on Amazon Web Services (AWS)
All databases and storage located in the United States
A concise view of the jobs, capabilities and integrations described in the recorded product sources.
Documented product formats, platforms and official distribution destinations. Availability can vary by region and plan.
A concise history of software releases and material product changes. Events appear only when a dated source supports what changed.
Showing the newest updates and meaningful milestones. Open an entry for its summary and source.
Decodable integrated PyFlink, the Python API for Apache Flink, into its platform to enable development teams to build scalable batch and streaming workloads, with a focus on AI use cases.
View source [9]Decodable announced integration of PyFlink support into its real-time data platform, adding a Python API for Apache Flink to enhance stream and batch processing for AI applications.
View source [9]Decodable integrated PyFlink support into its platform, enabling Python-based development of scalable batch and streaming workloads targeted at AI applications.
View source [9]Decodable integrated PyFlink, the Python API for Apache Flink, into its managed real-time data platform, enabling developers to author Flink pipelines in Python for batch, streaming, ELT, and AI workloads.
View source [9]Facts, answers, structured details, milestones and primary resource links cite this shared ledger. Each external page appears once; release tags from the same GitHub project are grouped under one release history.
These tools share a workflow, capability or audience with Decodable. They may complement it rather than replace it, and are not presented as integrations or endorsements.
Data encrypted at rest and in transit with TLS 1.2+
Developer and Team plans include a limited number of concurrent real-time previews; Enterprise plan includes unlimited previews
Make streaming data engineering easy
Cloud-native stream processing platform, powered by Apache Flink and Debezium
Supports SQL, Java, Python, and dbt integration
SOC2 Type II and GDPR compliant
Serverless-style workflow with no infrastructure provisioning required
Free tier available to start; scale as needed
Real-time applications including security and fraud detection, logistics, commerce, and social
Application developers, data engineers, and data scientists
Eric Sammer is Founder & CEO of Decodable
Backed by Venrock and Bain Capital
Sensitive data protected during transfer
Single platform spanning simple data movement to advanced stream processing
Decodable, Inc.
Process data between Kafka topics (transform formats, route, cleanse, mask, filter, aggregate)
Build stream processing pipelines in SQL or with the Apache Flink APIs
Define connections, streams, and pipelines via UI, CLI, APIs, or dbt
Fully managed cloud service (nothing to deploy or maintain)
Bring Your Own Cloud (BYOC) deployment mode available alongside fully hosted
Snowflake via pre-integrated Snowpipe Streaming API connector
Open source dbt-Decodable adapter to manage streaming and batch transformations in dbt
Apache Pinot real-time tables for streaming ingestion
Connects Confluent Cloud and Confluent Platform without replatforming
Real-time scenarios including user behavior analytics, fraud detection, and AI feature stores
SOC2 Type II, HIPAA, and GDPR compliant
Stateful stream processing with fully-managed Apache Flink
Process event and change data capture data using SQL
