DBMS > Datomic vs. LevelDB vs. Quasardb vs. SpatiaLite

System Properties Comparison Datomic vs. LevelDB vs. Quasardb vs. SpatiaLite

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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

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Distributed, high-performance timeseries database

Spatial extension of SQLite

Primary database model

Secondary database models

Relational DBMS

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

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	1.60
Rank	#149	Overall
	#3	Spatial DBMS

Website

www.datomic.com

github.com/google/leveldb

quasar.ai

www.gaia-gis.it/fossil/libspatialite/index

Technical documentation

docs.datomic.com

github.com/google/leveldb/blob/main/doc/index.md

doc.quasar.ai/master

www.gaia-gis.it/gaia-sins/spatialite_topics.html

Developer

Cognitect

Google

quasardb

Alessandro Furieri

Initial release

2012

2011

2009

2008

Current release

1.0.6735, June 2023

1.23, February 2021

3.14.1, January 2024

5.0.0, August 2020

License

Commercial or Open Source

commercial

limited edition free

Open Source

BSD

commercial

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

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

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++

Server operating systems

All OS with a Java VM

Illumos
Linux
OS X
Windows

BSD
Linux
OS X
Windows

server-less

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

integer and binary

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.

Secondary indexes

yes

with tags

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

RESTful HTTP API

HTTP API

Supported programming languages

Clojure
Java

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

.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

yes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

none

Sharding

consistent hashing

none

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

none

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

with automatic compression on writes

yes

by using LevelDB

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

Transient mode

yes

User concepts

Access control

Cryptographically strong user authentication and audit trail

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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