DBMS > Datomic vs. EsgynDB vs. HugeGraph vs. JSqlDb vs. Weaviate

System Properties Comparison Datomic vs. EsgynDB vs. HugeGraph vs. JSqlDb vs. Weaviate

Editorial information provided by DB-Engines

Name

JSqlDB seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

A fast-speed and highly-scalable Graph DBMS

JavaScript Query Language Database, stores JavaScript objects and primitives

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

Primary database model

Relational DBMS

Graph DBMS

Document store
Object oriented DBMS

Vector DBMS

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

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	1.73
Rank	#143	Overall
	#5	Vector DBMS

Website

www.datomic.com

www.esgyn.cn

github.com/hugegraph
hugegraph.apache.org

jsqldb.org (offline)

github.com/weaviate/weaviate
weaviate.io

Technical documentation

docs.datomic.com

hugegraph.apache.org/docs

weaviate.io/developers/weaviate

Developer

Cognitect

Esgyn

Baidu

Konrad von Backstrom

Weaviate B.V.

Initial release

2012

2015

2018

2019

Current release

1.0.6735, June 2023

0.9

0.8, December 2018

1.19, May 2023

License

Commercial or Open Source

commercial

limited edition free

commercial

Open Source

Apache Version 2.0

Open Source

commercial license available with Weaviate Enterprise

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, Clojure

C++, Java

Java

Server operating systems

All OS with a Java VM

Linux

Linux
macOS
Unix

Linux
macOS
Windows

Data scheme

yes

schema-free

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

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

also supports composite index and range index

yes

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

SQL

Support of SQL

yes

GraphQL is used as query language

APIs and other access methods

RESTful HTTP API

ADO.NET
JDBC
ODBC

Java API
RESTful HTTP API
TinkerPop Gremlin

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

Clojure
Java

All languages supporting JDBC/ODBC/ADO.Net

Groovy
Java
Python

JavaScript

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

yes

Transaction Functions

Java Stored Procedures

asynchronous Gremlin script jobs

functions in JavaScript

Triggers

By using transaction functions

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

Sharding

yes

depending on used storage backend, e.g. Cassandra and HBase

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

Multi-source replication between multi datacenters

yes

depending on used storage backend, e.g. Cassandra and HBase

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

edges in graph

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

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

using RocksDB

yes

In-memory capabilities

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

yes

recommended only for testing and development

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Users, roles and permissions

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,...
» more

Competitive advantages

Flexible deployment - Free, open source or fully-managed cloud vector database service...
» more

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...
» more

Licensing and pricing models

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

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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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