DBMS > EsgynDB vs. Hazelcast vs. Postgres-XL vs. Weaviate vs. XTDB

System Properties Comparison EsgynDB vs. Hazelcast vs. Postgres-XL vs. Weaviate vs. XTDB

Editorial information provided by DB-Engines

Name

Description

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

A widely adopted in-memory data grid

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

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

Secondary database models

Document store

JSON support with IMDG 3.12

Document store
Spatial DBMS

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

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	5.97
Rank	#57	Overall
	#6	Key-value stores

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	1.73
Rank	#143	Overall
	#5	Vector DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

www.esgyn.cn

hazelcast.com

www.postgres-xl.org

github.com/weaviate/weaviate
weaviate.io

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

Technical documentation

hazelcast.org/imdg/docs

www.postgres-xl.org/documentation

weaviate.io/developers/weaviate

www.xtdb.com/docs

Developer

Esgyn

Hazelcast

Weaviate B.V.

Juxt Ltd.

Initial release

2015

2008

2014

since 2012, originally named StormDB

2019

Current release

5.3.6, November 2023

10 R1, October 2018

1.19, May 2023

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses available

Open Source

Mozilla public license

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

C++, Java

Java

Clojure

Server operating systems

Linux

All OS with a Java VM

Linux
macOS

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

Data scheme

yes

schema-free

yes

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.

yes

the object must implement a serialization strategy

yes

XML type, but no XML query functionality

Secondary indexes

yes

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

yes

SQL

Support of SQL

yes

SQL-like query language

yes

distributed, parallel query execution

GraphQL is used as query language

limited SQL, making use of Apache Calcite

APIs and other access methods

ADO.NET
JDBC
ODBC

JCache
JPA
Memcached protocol
RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

GraphQL query language
RESTful HTTP/JSON API

HTTP REST
JDBC

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

JavaScript / TypeScript
Python

Clojure
Java

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Event Listeners, Executor Services

user defined functions

Triggers

yes

Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

yes

Replicated Map

yes

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

one or two-phase-commit; repeatable reads; read commited

ACID

MVCC

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

fine grained access rights according to SQL-standard

Role-based access control

fine grained access rights according to SQL-standard

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.
» 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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