DBMS > Dgraph vs. EsgynDB vs. OpenTSDB vs. OrigoDB vs. Trafodion

System Properties Comparison Dgraph vs. EsgynDB vs. OpenTSDB vs. OrigoDB vs. Trafodion

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

Distributed and scalable native Graph DBMS

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Scalable Time Series DBMS based on HBase

A fully ACID in-memory object graph database

Transactional SQL-on-Hadoop DBMS

Primary database model

Graph DBMS

Relational DBMS

Time Series DBMS

Document store
Object oriented DBMS

Relational DBMS

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

Score	1.53
Rank	#152	Overall
	#15	Graph DBMS

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	1.68
Rank	#142	Overall
	#12	Time Series DBMS

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Website

Technical documentation

dgraph.io/docs

opentsdb.net/docs/build/html/index.html

origodb.com/docs

trafodion.apache.org/documentation.html

Developer

Dgraph Labs, Inc.

Esgyn

currently maintained by Yahoo and other contributors

Robert Friberg et al

Apache Software Foundation, originally developed by HP

Initial release

2016

2015

2011

2009

under the name LiveDB

2014

Current release

2.3.0, February 2019

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

LGPL

Open Source

Apache 2.0

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

C++, Java

Java

C++, Java

Server operating systems

Linux
OS X
Windows

Linux

Linux
Windows

Linux

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

numeric data for metrics, strings for tags

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

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

ADO.NET
JDBC
ODBC

HTTP API
Telnet API

.NET Client API
HTTP API
LINQ

ADO.NET
JDBC
ODBC

Supported programming languages

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

All languages supporting JDBC/ODBC/ADO.Net

Erlang
Go
Java
Python
R
Ruby

.Net

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Java Stored Procedures

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

based on HBase

horizontal partitioning

client side managed; servers are not synchronized

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

Multi-source replication between multi datacenters

selectable replication factor

based on HBase

Source-replica replication

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

based on HBase

Immediate Consistency

Foreign keys

Referential integrity

yes

depending on model

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

Write ahead log

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Planned for future releases

fine grained access rights according to SQL-standard

Role based authorization

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

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