Apache Kudu Alternatives (January 2026)

Apache Kudu

Apache Kudu - Fast Analytics on Fast Data

https://kudu.apach.org/

A new open source Apache Hadoop ecosystem project, Apache Kudu completes Hadoop's storage layer to enable fast analytics on fast data

4.1/5

13+ reviews

Reviewed on:

G2
1.
Apache Pinotâ„¢
https://pinot.apach
.org/

Realtime distributed OLAP datastore

2.
Apache Eagle - Analyze Big Data Platforms For Security and Performance
https://eagle.apach
.org/

Apache Eagle - Analyze Big Data Platforms For Security and Performance

3.
Apache Arrow | Apache Arrow
https://arrow.apach
.org/

A cross-language development platform for in-memory analytics

4.
Apache Kafka
https://kafka.apach
.org/

Apache Kafka: A Distributed Streaming Platform.

5.
Apache Apex
https://apex.apach
.org/

Apex is an enterprise grade native YARN big data-in-motion platform that unifies stream processing as well as batch processing.

6.
RocksDB | A persistent key-value store | RocksDB
http://rocksd
.org/

RocksDB is an embeddable persistent key-value store for fast storage.

7.
Apache OODT - Distributed Data Management
https://oodt.apach
.org/

Apache Object Oriented Data Technology (OODT) is the smart way to integrate and archive your processes, your data, and its metadata. It facilitates the generation, processing, management, distribution, analysis of data management, data archiving, and data analytics systems allowing for the integration of data, computation, visualization and other components.

8.
ScyllaDB | Monstrously Fast + Scalable NoSQL
https://www.scyllad
.com/

ScyllaDB is the distributed database for data-intensive apps that require high performance and low latency.

9.
Apache Beam®
https://beam.apach
.org/

Apache Beam is an open source, unified model and set of language-specific SDKs for defining and executing data processing workflows, and also data ingestion and integration flows, supporting Enterprise Integration Patterns (EIPs) and Domain Specific Languages (DSLs). Dataflow pipelines simplify the mechanics of large-scale batch and streaming data processing and can run on a number of runtimes like Apache Flink, Apache Spark, and Google Cloud Dataflow (a cloud service). Beam also brings DSL in different languages, allowing users to easily implement their data integration processes.