DBMS > Datomic vs. Hypertable vs. NSDb vs. TerminusDB

System Properties Comparison Datomic vs. Hypertable vs. NSDb vs. TerminusDB

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Editorial information provided by DB-Engines

Name

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

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

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Secondary database models

Document store
RDF store

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
	#41	Time Series DBMS

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Website

www.datomic.com

nsdb.io

terminusdb.com

Technical documentation

docs.datomic.com

nsdb.io/Architecture

terminusdb.github.io/terminusdb/#

Developer

Cognitect

Hypertable Inc.

DataChemist Ltd.

Initial release

2012

2009

2017

2018

Current release

1.0.6735, June 2023

0.9.8.11, March 2016

11.0.0, January 2023

License

Commercial or Open Source

commercial

limited edition free

Open Source

GNU version 3. Commercial license available

Open Source

Apache Version 2.0

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, Clojure

C++

Java, Scala

Prolog, Rust

Server operating systems

All OS with a Java VM

Linux
OS X
Windows

an inofficial Windows port is available

Linux
macOS

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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

restricted

only exact value or prefix value scans

all fields are automatically indexed

SQL

Support of SQL

SQL-like query language

SQL-like query language (WOQL)

APIs and other access methods

RESTful HTTP API

C++ API
Thrift

gRPC
HTTP REST
WebSocket

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

Clojure
Java

C++
Java
Perl
PHP
Python
Ruby

Java
Scala

JavaScript
Python

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

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

Sharding

Graph Partitioning

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

Journaling Streams

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

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

Using Apache Lucene

yes

in-memory journaling

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

Role-based access control

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