DBMS > Datomic vs. EventStoreDB vs. Lovefield vs. Quasardb

System Properties Comparison Datomic vs. EventStoreDB vs. Lovefield vs. Quasardb

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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

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

Embeddable relational database for web apps written in pure JavaScript

Distributed, high-performance timeseries database

Primary database model

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

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	1.10
Rank	#179	Overall
	#1	Event Stores

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Website

www.datomic.com

www.eventstore.com

google.github.io/lovefield

quasar.ai

Technical documentation

docs.datomic.com

developers.eventstore.com

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

doc.quasar.ai/master

Developer

Cognitect

Event Store Limited

Google

quasardb

Initial release

2012

2014

2009

Current release

1.0.6735, June 2023

21.2, February 2021

2.1.12, February 2017

3.14.1, January 2024

License

Commercial or Open Source

commercial

limited edition free

Open Source

Apache 2.0

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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

JavaScript

C++

Server operating systems

All OS with a Java VM

Linux
Windows

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

tested with Chrome, Firefox, IE, Safari

BSD
Linux
OS X
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

integer and binary

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

with tags

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

SQL-like query language

APIs and other access methods

RESTful HTTP API

HTTP API

Supported programming languages

Clojure
Java

JavaScript

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

yes

Transaction Functions

Triggers

By using transaction functions

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

none

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

none

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

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, by using IndexedDB or the cloud service Firebase Realtime Database

yes

by using LevelDB

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

Transient mode

User concepts

Access control

Cryptographically strong user authentication and audit trail

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