DBMS > Datomic vs. GeoSpock vs. HugeGraph vs. RocksDB vs. Teradata Aster

System Properties Comparison Datomic vs. GeoSpock vs. HugeGraph vs. RocksDB vs. Teradata Aster

Editorial information provided by DB-Engines

Name

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

Teradata Aster has been integrated into other Teradata systems and therefore will be 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

A fast-speed and highly-scalable Graph DBMS

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Platform for big data analytics on multistructured data sources and types

Primary database model

Secondary database models

Time Series DBMS

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

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

www.datomic.com

geospock.com

github.com/hugegraph
hugegraph.apache.org

rocksdb.org

Technical documentation

docs.datomic.com

hugegraph.apache.org/docs

github.com/facebook/rocksdb/wiki

Developer

Cognitect

GeoSpock

Baidu

Facebook, Inc.

Teradata

Initial release

2012

2018

2013

2005

Current release

1.0.7075, December 2023

2.0, September 2019

0.9

9.2.1, May 2024

License

Commercial or Open Source

commercial

limited edition free

commercial

Open Source

Apache Version 2.0

Open Source

BSD

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

Java, Javascript

Java

C++

Server operating systems

All OS with a Java VM

hosted

Linux
macOS
Unix

Linux

Data scheme

yes

schema-free

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

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

in Aster File Store

Secondary indexes

yes

temporal, categorical

yes

also supports composite index and range index

yes

SQL

Support of SQL

ANSI SQL for query only (using Presto)

yes

APIs and other access methods

RESTful HTTP API

JDBC

Java API
RESTful HTTP API
TinkerPop Gremlin

C++ API
Java API

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

Clojure
Java

Groovy
Java
Python

C
C++
Go
Java
Perl
Python
Ruby

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

yes

Transaction Functions

asynchronous Gremlin script jobs

R packages

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

yes

depending on used storage backend, e.g. Cassandra and HBase

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

yes

depending on used storage backend, e.g. Cassandra and HBase

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

edges in graph

Transaction concepts

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

ACID

yes

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

Access rights for users can be defined per table

Users, roles and permissions

fine grained access rights according to SQL-standard

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