DBMS > AgensGraph vs. Citus vs. Google Cloud Spanner vs. Postgres-XL vs. STSdb

System Properties Comparison AgensGraph vs. Citus vs. Google Cloud Spanner vs. Postgres-XL vs. STSdb

Editorial information provided by DB-Engines

Name

Description

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

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Graph DBMS
Relational DBMS

Relational DBMS

Key-value store

Secondary database models

Document store

Document store
Spatial DBMS

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

Score	0.20
Rank	#321	Overall
	#27	Graph DBMS
	#143	Relational DBMS

Score	2.21
Rank	#118	Overall
	#56	Relational DBMS

Score	2.89
Rank	#103	Overall
	#52	Relational DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

bitnine.net/agensgraph

www.citusdata.com

cloud.google.com/spanner

www.postgres-xl.org

github.com/STSSoft/STSdb4

Technical documentation

bitnine.net/documentation

docs.citusdata.com

cloud.google.com/spanner/docs

www.postgres-xl.org/documentation

Developer

Bitnine Global Inc.

Google

STS Soft SC

Initial release

2016

2010

2017

2014

since 2012, originally named StormDB

2011

Current release

2.1, December 2018

8.1, December 2018

10 R1, October 2018

4.0.8, September 2015

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

AGPL, commercial license also available

commercial

Open Source

Mozilla public license

Open Source

GPLv2, commercial license available

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

Server operating systems

Linux
OS X
Windows

Linux

hosted

Linux
macOS

Windows

Data scheme

depending on used data model

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

specific XML type available, but no XML query functionality

yes

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

standard, with numerous extensions

yes

Query statements complying to ANSI 2011

yes

distributed, parallel query execution

APIs and other access methods

Cypher Query Language
JDBC

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

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

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

.NET Client API

Supported programming languages

C
Java
JavaScript
Python

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Go
Java
JavaScript (Node.js)
Python

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C#
Java

Server-side scripts

Stored procedures

yes

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

other methods possible by using 3rd party extensions

Multi-source replication with 3 replicas for regional instances.

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

yes

Transaction concepts

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

ACID

Strict serializable isolation

ACID

MVCC

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

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