DBMS > Datomic vs. GeoMesa vs. LokiJS vs. Microsoft Azure SQL Database

System Properties Comparison Datomic vs. GeoMesa vs. LokiJS vs. Microsoft Azure SQL Database

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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

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

In-memory JavaScript DBMS

Database as a Service offering with high compatibility to Microsoft SQL Server

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	0.49
Rank	#260	Overall
	#42	Document stores

Score	76.78
Rank	#16	Overall
	#11	Relational DBMS

Website

www.datomic.com

www.geomesa.org

github.com/techfort/LokiJS

azure.microsoft.com/en-us/products/azure-sql/database

Technical documentation

docs.datomic.com

www.geomesa.org/documentation/stable/user/index.html

techfort.github.io/LokiJS

docs.microsoft.com/en-us/azure/azure-sql

Developer

Cognitect

CCRi and others

Microsoft

Initial release

2012

2014

2010

Current release

1.0.7075, December 2023

5.0.0, May 2024

V12

License

Commercial or Open Source

commercial

limited edition free

Open Source

Apache License 2.0

Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java, Clojure

Scala

JavaScript

C++

Server operating systems

All OS with a Java VM

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

hosted

Data scheme

yes

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

Secondary indexes

yes

via views

yes

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP API

JavaScript API

ADO.NET
JDBC
ODBC

Supported programming languages

Clojure
Java

JavaScript

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Transaction Functions

View functions in JavaScript

Transact SQL

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

depending on storage layer

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

depending on storage layer

none

yes, with always 3 replicas available

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

depending on storage layer

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

atomic operations within a single collection possible

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

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

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

depending on storage layer

yes

User concepts

Access control

yes

depending on the DBMS used for storage

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

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