Matchups: Apache Pulsar vs Amazon Kinesis | Real Time Data Platforms Comparison

Overview

Apache Pulsar is an open-source, distributed messaging and streaming platform with a segmented log architecture, optimized for multi-tenancy and tiered storage.

Amazon Kinesis is a fully managed, serverless streaming service on AWS, designed for real-time data ingestion and processing using a shard-based architecture.

Both support large-scale streaming: Pulsar offers flexibility and multi-tenant isolation, Kinesis provides managed simplicity and AWS integration.

Fun Fact: Pulsar’s tiered storage was designed to handle massive event retention cost-effectively!

Section 1 - Architecture

Pulsar publish/subscribe (Java):

PulsarClient client = PulsarClient.builder() .serviceUrl("pulsar://localhost:6650").build(); Producer producer = client.newProducer().topic("topic").create(); producer.send("event".getBytes());

Kinesis publish (Python):

import boto3 kinesis = boto3.client('kinesis') kinesis.put_record( StreamName='stream', Data='event', PartitionKey='key' )

Pulsar’s architecture decouples compute (brokers) and storage (Apache BookKeeper), using segmented logs for dynamic scaling and multi-tenancy. This enables tenant isolation and tiered storage (e.g., offloading to S3). Kinesis employs a shard-based model, with streams split into shards, fully managed by AWS, prioritizing simplicity over customization. Pulsar’s flexibility supports complex deployments, while Kinesis’ serverless design reduces operational overhead.

Scenario: A 500K-event/sec IoT pipeline—Pulsar ensures tenant isolation for multiple clients, Kinesis simplifies AWS-native ingestion.

Pro Tip: Use Pulsar’s subscription modes (exclusive, shared) for flexible event consumption!

Section 2 - Performance

Pulsar achieves 500K events/sec with 15ms latency (e.g., 10 brokers, SSDs), leveraging segmented logs and BookKeeper for consistent tail latency across tenants.

Kinesis supports 500K events/sec with 20ms latency (e.g., 100 shards), optimized for bursty workloads but limited by shard capacity and AWS throttling.

Scenario: A 50K-user real-time dashboard—Pulsar maintains low latency under variable loads, Kinesis excels in AWS-integrated, bursty ingestion. Pulsar’s performance is tenant-optimized, Kinesis is cloud-optimized.

Key Insight: Kinesis’ enhanced fan-out reduces latency for multiple consumers!

Section 3 - Scalability

Pulsar scales across 50+ brokers, handling 5TB+ datasets, with BookKeeper enabling independent storage scaling and tiered storage for cost efficiency.

Kinesis scales by adding shards, supporting 1TB+ datasets with automatic shard management, constrained by AWS account limits (e.g., 500 shards/region).

Scenario: A 2TB event store—Pulsar scales with storage tiering for long-term retention, Kinesis automates scaling but incurs per-shard costs. Pulsar is flexible, Kinesis is automated.

Advanced Tip: Use Pulsar’s tiered storage to archive events to S3 for cost savings!

Section 4 - Ecosystem and Use Cases

Pulsar integrates with Pulsar Functions, IO connectors, and Presto for stream processing, ideal for multi-tenant IoT and messaging (e.g., 10K tenants at Comcast).

Kinesis pairs with AWS Lambda, Kinesis Data Analytics, and Firehose for serverless workflows, suited for real-time monitoring (e.g., 100K sensor events/sec at AWS customers).

Pulsar powers flexible messaging (e.g., Yahoo’s pub/sub), Kinesis excels in AWS-native apps (e.g., IoT analytics). Pulsar is multi-tenant, Kinesis is AWS-centric.

Example: Comcast uses Pulsar for IoT; AWS IoT uses Kinesis for real-time data!

Section 5 - Comparison Table

Aspect	Apache Pulsar	Amazon Kinesis
Architecture	Segmented, decoupled	Shard-based, serverless
Performance	500K events/sec, 15ms	500K events/sec, 20ms
Scalability	Storage-separated	Shard-based, auto
Ecosystem	Functions, Presto	Lambda, Firehose
Best For	Multi-tenant, IoT	AWS apps, monitoring

Pulsar enhances multi-tenant flexibility; Kinesis simplifies AWS integration.

Conclusion

Apache Pulsar and Amazon Kinesis are robust streaming platforms with distinct strengths. Pulsar excels in multi-tenant, flexible messaging with decoupled storage, ideal for IoT and diverse workloads. Kinesis is best for AWS-native, serverless applications requiring real-time ingestion and minimal management.

Choose based on needs: Pulsar for multi-tenancy and storage efficiency, Kinesis for AWS ecosystems and simplicity. Optimize with Pulsar Functions for lightweight processing or Kinesis Data Analytics for real-time insights. Hybrid setups (e.g., Pulsar for messaging, Kinesis for AWS endpoints) are feasible.

Pro Tip: Use Kinesis Data Firehose to stream events to Redshift for analytics!

Tech Matchups: Apache Pulsar vs. Amazon Kinesis