DBMS > Datomic vs. HyperSQL vs. Percona Server for MongoDB vs. Transwarp Hippo

System Properties Comparison Datomic vs. HyperSQL vs. Percona Server for MongoDB vs. Transwarp Hippo

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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

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

Primary database model

Relational DBMS

Document store

Vector 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	0.52
Rank	#254	Overall
	#39	Document stores

Score	0.00
Rank	#383	Overall
	#13	Vector DBMS

Website

www.datomic.com

hsqldb.org

www.percona.com/mongodb/software/percona-server-for-mongodb

www.transwarp.cn/en/subproduct/hippo

Technical documentation

docs.datomic.com

hsqldb.org/web/hsqlDocsFrame.html

docs.percona.com/percona-distribution-for-mongodb

Developer

Cognitect

Percona

Initial release

2012

2001

2015

2023

Current release

1.0.6735, June 2023

2.7.2, June 2023

3.4.10-2.10, November 2017

1.0, May 2023

License

Commercial or Open Source

commercial

limited edition free

Open Source

based on BSD license

Open Source

GPL Version 2

commercial

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

Java

C++

Server operating systems

All OS with a Java VM

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

Linux

Linux
macOS

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Vector, Numeric and 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

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP API

HTTP API

JDBC via HTTP
JDBC
ODBC

proprietary protocol using JSON

RESTful HTTP API

Supported programming languages

Clojure
Java

All languages supporting JDBC/ODBC
Java

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

C++
Java
Python

Server-side scripts

Stored procedures

yes

Transaction Functions

Java, SQL

JavaScript

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

Source-replica 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
Immediate 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

via In-Memory Engine

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles

Role based access control and fine grained access rights

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