DBMS > JanusGraph vs. Riak KV vs. Weaviate vs. XTDB

System Properties Comparison JanusGraph vs. Riak KV vs. Weaviate vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

Distributed, fault tolerant key-value store

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

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Graph DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Vector DBMS

Document store

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

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Score	1.73
Rank	#143	Overall
	#5	Vector DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

janusgraph.org

github.com/weaviate/weaviate
weaviate.io

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

docs.janusgraph.org

www.tiot.jp/riak-docs/riak/kv/latest

weaviate.io/developers/weaviate

www.xtdb.com/docs

Developer

Linux Foundation; originally developed as Titan by Aurelius

OpenSource, formerly Basho Technologies

Weaviate B.V.

Juxt Ltd.

Initial release

2017

2009

2019

Current release

0.6.3, February 2023

3.2.0, December 2022

1.19, May 2023

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache version 2, commercial enterprise edition

Open Source

commercial license available with Weaviate Enterprise

Open Source

MIT License

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

Java

Erlang

Clojure

Server operating systems

Linux
OS X
Unix
Windows

Linux
OS X

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free

yes, maps to GraphQL interface

schema-free

Typing

predefined data types such as float or date

yes

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

yes, extensible-data-notation format

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

restricted

yes

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

yes

SQL

Support of SQL

GraphQL is used as query language

limited SQL, making use of Apache Calcite

APIs and other access methods

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

HTTP API
Native Erlang Interface

GraphQL query language
RESTful HTTP/JSON API

HTTP REST
JDBC

Supported programming languages

Clojure
Java
Python

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

JavaScript / TypeScript
Python

Clojure
Java

Server-side scripts

Stored procedures

yes

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Sharding

no "single point of failure"

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

yes

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

links between data sets can be stored

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

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

yes

User concepts

Access control

User authentification and security via Rexster Graph Server

yes, using Riak Security

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...
» more

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.

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More resources

DB-Engines blog posts

Weaviate, an ANN Database with CRUD support
2 February 2021, Etienne Dilocker, SeMI Technologies (sponsor)

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