DBMS > BoltDB vs. RocksDB vs. Sphinx vs. Weaviate vs. YTsaurus

System Properties Comparison BoltDB vs. RocksDB vs. Sphinx vs. Weaviate vs. YTsaurus

Editorial information provided by DB-Engines

Name

Description

An embedded key-value store for Go.

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

Open source search engine for searching in data from different sources, e.g. relational databases

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

YTsaurus is an open source platform for distributed storage and processing.

Primary database model

Key-value store

Search engine

Vector DBMS

Document store
Key-value store

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

Score	0.80
Rank	#215	Overall
	#31	Key-value stores

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	5.95
Rank	#55	Overall
	#5	Search engines

Score	1.52
Rank	#153	Overall
	#5	Vector DBMS

Score	0.21
Rank	#324	Overall
	#45	Document stores
	#48	Key-value stores

Website

github.com/boltdb/bolt

rocksdb.org

sphinxsearch.com

github.com/weaviate/weaviate
weaviate.io

ytsaurus.tech

Technical documentation

github.com/facebook/rocksdb/wiki

sphinxsearch.com/docs

weaviate.io/developers/weaviate

ytsaurus.tech/docs/en

Developer

Facebook, Inc.

Sphinx Technologies Inc.

Weaviate B.V.

Yandex

Initial release

2013

2001

2019

2023

Current release

9.2.1, May 2024

3.5.1, February 2023

1.19, May 2023

License

Commercial or Open Source

Open Source

MIT License

Open Source

BSD

Open Source

GPL version 2, commercial licence available

Open Source

commercial license available with Weaviate Enterprise

Open Source

Apache License, Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Ubuntu

Data scheme

schema-free

yes

yes, maps to GraphQL interface

Typing

predefined data types such as float or date

yes

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

yes

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.

Secondary indexes

yes

full-text index on all search fields

yes

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

SQL

Support of SQL

SQL-like query language (SphinxQL)

GraphQL is used as query language

YQL, an SQL-based language, is supported

APIs and other access methods

C++ API
Java API

Proprietary protocol

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

C
C++
Go
Java
Perl
Python
Ruby

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

JavaScript / TypeScript
Python

C++
Go
Java
JavaScript
Python

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Sharding

Partitioning is done manually, search queries against distributed index is supported

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Sphinx index.

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

API Keys
OpenID Connect Discovery

Access Control Lists

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.
» more

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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.