DBMS > AgensGraph vs. Cassandra vs. OrigoDB vs. TimescaleDB

System Properties Comparison AgensGraph vs. Cassandra vs. OrigoDB vs. TimescaleDB

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Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

A fully ACID in-memory object graph database

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Graph DBMS
Relational DBMS

Wide column store

Document store
Object oriented DBMS

Time Series DBMS

Secondary database models

Vector DBMS

starting with release V5

Relational DBMS

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

Score	0.16
Rank	#333	Overall
	#30	Graph DBMS
	#146	Relational DBMS

Score	103.86
Rank	#12	Overall
	#1	Wide column stores

Score	0.03
Rank	#378	Overall
	#51	Document stores
	#18	Object oriented DBMS

Score	4.87
Rank	#74	Overall
	#4	Time Series DBMS

Website

bitnine.net/agensgraph

cassandra.apache.org

origodb.com

www.timescale.com

Technical documentation

bitnine.net/documentation

cassandra.apache.org/doc/latest

origodb.com/docs

docs.timescale.com

Developer

Bitnine Global Inc.

Apache Software Foundation

Apache top level project, originally developped by Facebook

Robert Friberg et al

Timescale

Initial release

2016

2008

2009

under the name LiveDB

2017

Current release

2.1, December 2018

4.1.3, July 2023

2.13.0, November 2023

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

Apache version 2

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Astra DB: Multi-cloud DBaaS built on Apache Cassandra.

Implementation language

Java

Server operating systems

Linux
OS X
Windows

BSD
Linux
OS X
Windows

Linux
Windows

Linux
OS X
Windows

Data scheme

depending on used data model

schema-free

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

yes

Secondary indexes

yes

restricted

only equality queries, not always the best performing solution

yes

SQL

Support of SQL

yes

SQL-like SELECT, DML and DDL statements (CQL)

yes

full PostgreSQL SQL syntax

APIs and other access methods

Cypher Query Language
JDBC

Proprietary protocol

CQL (Cassandra Query Language, an SQL-like language)
Thrift

.NET Client API
HTTP API
LINQ

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

C
Java
JavaScript
Python

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

.Net

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

no "single point of failure"

horizontal partitioning

client side managed; servers are not synchronized

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

Representation of geographical distribution of servers is possible

Source-replica replication

Source-replica replication with hot standby and reads on replicas

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

can be individually decided for each write operation

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

Atomicity and isolation are supported for single operations

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

fine grained access rights according to SQL-standard

Access rights for users can be defined per object

Role based authorization

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

Apache Cassandra is the leading NoSQL, distributed database management system, well...
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Competitive advantages

No single point of failure ensures 100% availability . Operational simplicity for...
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Typical application scenarios

Internet of Things (IOT), fraud detection applications, recommendation engines, product...
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Key customers

Apple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best...
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Market metrics

Cassandra is used by 40% of the Fortune 100.
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Licensing and pricing models

Apache licenseÂ Pricing for commercial distributions provided by DataStax and available...
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