DBMS > Apache Druid vs. RocksDB vs. Rockset vs. Weaviate

System Properties Comparison Apache Druid vs. RocksDB vs. Rockset vs. Weaviate

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Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

A scalable, reliable search and analytics service in the cloud, built on RocksDB

An AI-native realtime vector database engine that integrates scalable machine learning models.

Primary database model

Relational DBMS
Time Series DBMS

Key-value store

Document store

Vector DBMS

Secondary database models

Relational DBMS
Search engine

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	3.29
Rank	#95	Overall
	#49	Relational DBMS
	#7	Time Series DBMS

Score	4.00
Rank	#84	Overall
	#11	Key-value stores

Score	0.84
Rank	#209	Overall
	#35	Document stores

Score	1.89
Rank	#138	Overall
	#4	Vector DBMS

Website

druid.apache.org

rocksdb.org

rockset.com

github.com/weaviate/weaviate
weaviate.io

Technical documentation

druid.apache.org/docs/latest/design

github.com/facebook/rocksdb/wiki

docs.rockset.com

weaviate.io/developers/weaviate

Developer

Apache Software Foundation and contributors

Facebook, Inc.

Rockset

Weaviate B.V.

Initial release

2012

2013

2019

Current release

29.0.1, April 2024

8.11.4, April 2024

1.19, May 2023

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

BSD

commercial

Open Source

commercial license available with Weaviate Enterprise

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++

Server operating systems

Linux
OS X
Unix

Linux

hosted

Data scheme

yes

schema-less columns are supported

schema-free

yes, maps to GraphQL interface

Typing

predefined data types such as float or date

yes

dynamic typing

yes

string, int, float, geo point, date, cross reference, fuzzy references

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

ingestion from XML files supported

Secondary indexes

yes

all fields are automatically indexed

yes

all data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed

SQL

Support of SQL

SQL for querying

Read-only SQL queries, including JOINs

GraphQL is used as query language

APIs and other access methods

JDBC
RESTful HTTP/JSON API

C++ API
Java API

HTTP REST

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C
C++
Go
Java
Perl
Python
Ruby

Go
Java
JavaScript (Node.js)
Python

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

horizontal partitioning

Automatic sharding

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Access rights for users and organizations can be defined via Rockset console

API Keys
OpenID Connect Discovery

More information provided by the system vendor

Specific characteristics

Weaviate is an open source vector database that is robust, scalable, cloud-native,...
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Competitive advantages

Flexible deployment - Free, open source or fully-managed cloud vector database service...
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Typical application scenarios

As a database supporting the development of generative AI and semantic search applications...
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Key customers

All companies that have data.
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Market metrics

As of mid 2023: Over 2 million open source downloads 3500+ Weaviate Slack community...
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Licensing and pricing models

Weaviate is open-source, and free to use. Weaviate is also available as a fully managed...
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