DBMS > Datomic vs. Dgraph vs. Sadas Engine vs. TigerGraph

System Properties Comparison Datomic vs. Dgraph vs. Sadas Engine vs. TigerGraph

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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

Distributed and scalable native Graph DBMS

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

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

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Score	1.83
Rank	#139	Overall
	#13	Graph DBMS

Website

Technical documentation

docs.datomic.com

dgraph.io/docs

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

docs.tigergraph.com

Developer

Cognitect

Dgraph Labs, Inc.

SADAS s.r.l.

Initial release

2012

2016

2006

2017

Current release

1.0.6735, June 2023

8.0

License

Commercial or Open Source

commercial

limited edition free

Open Source

Apache 2.0

commercial

free trial version available

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

C++

Server operating systems

All OS with a Java VM

Linux
OS X
Windows

AIX
Linux
Windows

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

SQL

Support of SQL

yes

SQL-like query language (GSQL)

APIs and other access methods

RESTful HTTP API

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

JDBC
ODBC
Proprietary protocol

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

Clojure
Java

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

.Net
C
C#
C++
Groovy
Java
PHP
Python

C++
Java

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

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

yes

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

Synchronous replication via Raft

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

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

managed by 'Learn by Usage'

User concepts

Access control

Planned for future releases

Access rights for users, groups and roles according to SQL-standard

Role-based access control

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