DBMS > Datomic vs. HyperSQL vs. Hypertable vs. Hyprcubd vs. SWC-DB

System Properties Comparison Datomic vs. HyperSQL vs. Hypertable vs. Hyprcubd vs. SWC-DB

Editorial information provided by DB-Engines

Name

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

Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

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

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

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

Serverless Time Series DBMS

A high performance, scalable Wide Column DBMS

Primary database model

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	3.49
Rank	#87	Overall
	#47	Relational DBMS

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

www.datomic.com

hsqldb.org

hyprcubd.com (offline)

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

docs.datomic.com

hsqldb.org/web/hsqlDocsFrame.html

Developer

Cognitect

Hypertable Inc.

Hyprcubd, Inc.

Alex Kashirin

Initial release

2012

2001

2009

2020

Current release

1.0.6735, June 2023

2.7.2, June 2023

0.9.8.11, March 2016

0.5, April 2021

License

Commercial or Open Source

commercial

limited edition free

Open Source

based on BSD license

Open Source

GNU version 3. Commercial license available

commercial

Open Source

GPL V3

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

C++

Server operating systems

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Linux
OS X
Windows

an inofficial Windows port is available

hosted

Linux

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

time, int, uint, float, 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

restricted

only exact value or prefix value scans

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

RESTful HTTP API

HTTP API

JDBC via HTTP
JDBC
ODBC

C++ API
Thrift

gRPC (https)

Proprietary protocol
Thrift

Supported programming languages

Clojure
Java

All languages supporting JDBC/ODBC
Java

C++
Java
Perl
PHP
Python
Ruby

C++

Server-side scripts

Stored procedures

yes

Transaction Functions

Java, 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

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

none

selectable replication factor on file system level

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

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

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

User concepts

Access control

fine grained access rights according to SQL-standard

token access

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