DBMS > Datomic vs. GeoSpock vs. Hypertable vs. JaguarDB

System Properties Comparison Datomic vs. GeoSpock vs. Hypertable vs. JaguarDB

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Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

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

Spatial and temporal data processing engine for extreme data scale

An open source BigTable implementation based on distributed file systems such as Hadoop

Performant, highly scalable DBMS for AI and IoT applications

Primary database model

Relational DBMS

Wide column store

Key-value store
Vector DBMS

Secondary database models

Time Series DBMS

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

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Website

www.datomic.com

geospock.com

www.jaguardb.com

Technical documentation

docs.datomic.com

www.jaguardb.com/support.html

Developer

Cognitect

GeoSpock

Hypertable Inc.

DataJaguar, Inc.

Initial release

2012

2009

2015

Current release

1.0.6735, June 2023

2.0, September 2019

0.9.8.11, March 2016

3.3 July 2023

License

Commercial or Open Source

commercial

limited edition free

commercial

Open Source

GNU version 3. Commercial license available

Open Source

GPL V3.0

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

Java, Javascript

C++

the server part. Clients available in other languages

Server operating systems

All OS with a Java VM

hosted

Linux
OS X
Windows

an inofficial Windows port is available

Linux

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.

Secondary indexes

yes

temporal, categorical

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

ANSI SQL for query only (using Presto)

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

APIs and other access methods

RESTful HTTP API

JDBC

C++ API
Thrift

JDBC
ODBC

Supported programming languages

Clojure
Java

C++
Java
Perl
PHP
Python
Ruby

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes

Transaction Functions

Triggers

By using transaction functions

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

Automatic sharding

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

selectable replication factor on file system level

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

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

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

User concepts

Access control

Access rights for users can be defined per table

rights management via user accounts

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