DBMS > EventStoreDB vs. Hazelcast vs. KairosDB vs. Lovefield vs. openGauss

System Properties Comparison EventStoreDB vs. Hazelcast vs. KairosDB vs. Lovefield vs. openGauss

Editorial information provided by DB-Engines

Name

Description

Industrial-strength, open-source database solution built from the ground up for event sourcing.

A widely adopted in-memory data grid

Distributed Time Series DBMS based on Cassandra or H2

Embeddable relational database for web apps written in pure JavaScript

An enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by Huawei

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	1.10
Rank	#179	Overall
	#1	Event Stores

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

Score	0.62
Rank	#239	Overall
	#20	Time Series DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	1.08
Rank	#183	Overall
	#84	Relational DBMS

Website

www.eventstore.com

hazelcast.com

github.com/kairosdb/kairosdb

google.github.io/lovefield

gitee.com/opengauss
opengauss.org

Technical documentation

developers.eventstore.com

hazelcast.org/imdg/docs

kairosdb.github.io

github.com/google/lovefield/blob/master/docs/spec_index.md

docs.opengauss.org/en
gitee.com/opengauss/docs

Developer

Event Store Limited

Hazelcast

Google

Huawei and openGauss community

Initial release

2012

2008

2013

2014

2019

Current release

21.2, February 2021

5.3.6, November 2023

1.2.2, November 2018

2.1.12, February 2017

3.0, March 2022

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

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

JavaScript

C, C++, Java

Server operating systems

Linux
Windows

All OS with a Java VM

Linux
OS X
Windows

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

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.

yes

the object must implement a serialization strategy

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

ANSI SQL 2011

APIs and other access methods

JCache
JPA
Memcached protocol
RESTful HTTP API

Graphite protocol
HTTP REST
Telnet API

JDBC
ODBC

Supported programming languages

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

Java
JavaScript

Node.js
PHP
Python

JavaScript

C
C++
Java

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

yes

Triggers

yes

Events

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

none

horizontal partitioning (by range, list and hash)

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Replicated Map

selectable replication factor

based on Cassandra

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

using MemoryDB

User concepts

Access control

Role-based access control

simple password-based access control

Access rights for users, groups and roles according to SQL-standard

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