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DirectoryData & AnalyticsStreaming & Real-Time AnalyticsPulsar

Pulsar

About Pulsar

Apache Pulsar is an open-source, distributed messaging and streaming platform built for the cloud. It is described as an all-in-one messaging and streaming platform. Messages can be consumed and acknowledged individually or as streams. Its layered architecture allows scaling across hundreds of nodes without data reshuffling. Features include multi-tenancy, geo-replication, tiered storage, and support for six official client languages. It supports up to one million unique topics.

Used for

  • Submitting tasks to run and ensuring execution including error handling.
  • Using topics for indirect API communication among micro-services.
  • Running mission-critical applications requiring failure resiliency.
  • Streaming data in or out via third-party connectors such as MySQL, Elasticsearch, and Cassandra.

Who it is for

  • Has a user base spanning small companies and large enterprises.

From Pulsar'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 Pulsar. 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

pulsar.apache.org
CategoryData & Analytics
SubcategoryStreaming & Real-Time Analytics
PricingOpen source

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