DBMS > Datomic vs. Ehcache vs. Lovefield vs. openGemini

System Properties Comparison Datomic vs. Ehcache vs. Lovefield vs. openGemini

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Editorial information provided by DB-Engines

Name

Description

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

A widely adopted Java cache with tiered storage options

Embeddable relational database for web apps written in pure JavaScript

An open source distributed Time Series DBMS with high concurrency, high performance, and high scalability

Primary database model

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

Score	1.55
Rank	#144	Overall
	#67	Relational DBMS

Score	4.79
Rank	#66	Overall
	#8	Key-value stores

Score	0.22
Rank	#306	Overall
	#138	Relational DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Website

www.datomic.com

www.ehcache.org

google.github.io/lovefield

www.opengemini.org
github.com/openGemini

Technical documentation

docs.datomic.com

www.ehcache.org/documentation

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

docs.opengemini.org/guide

Developer

Cognitect

Terracotta Inc, owned by Software AG

Google

Huawei and openGemini community

Initial release

2012

2009

2014

2022

Current release

1.0.7180, July 2024

3.10.0, March 2022

2.1.12, February 2017

1.1, July 2023

License

Commercial or Open Source

commercial

limited edition free

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache 2.0

Open Source

Apache 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

Java, Clojure

Java

JavaScript

Server operating systems

All OS with a Java VM

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

tested with Chrome, Firefox, IE, Safari

Linux
Windows

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

Integer, Float, Boolean, String

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

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

SQL-like query language

APIs and other access methods

RESTful HTTP API

JCache

HTTP REST

Supported programming languages

Clojure
Java

Java

JavaScript

C
C++
Go
Java
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

yes

Transaction Functions

Triggers

By using transaction functions

yes

Cache Event Listeners

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

Sharding

by using Terracotta Server

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

yes

by using Terracotta Server

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Tunable Consistency (Strong, Eventual, Weak)

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

supports JTA and can work as an XA resource

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 a tiered cache-storage approach

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

recommended only for testing and development

yes

using MemoryDB

yes

User concepts

Access control

Administrators and common users accounts

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