DBMS > AgensGraph vs. Microsoft Azure Cosmos DB vs. Splice Machine vs. WakandaDB

System Properties Comparison AgensGraph vs. Microsoft Azure Cosmos DB vs. Splice Machine vs. WakandaDB

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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

Globally distributed, horizontally scalable, multi-model database service

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Graph DBMS
Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Object oriented DBMS

Secondary database models

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	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

bitnine.net/agensgraph

azure.microsoft.com/services/cosmos-db

splicemachine.com

wakanda.github.io

Technical documentation

bitnine.net/documentation

learn.microsoft.com/azure/cosmos-db

splicemachine.com/how-it-works

wakanda.github.io/doc

Developer

Bitnine Global Inc.

Microsoft

Splice Machine

Wakanda SAS

Initial release

2016

2014

2012

Current release

2.1, December 2018

3.1, March 2021

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

Open Source

AGPL 3.0, commercial license available

Open Source

AGPLv3, extended commercial license available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++, JavaScript

Server operating systems

Linux
OS X
Windows

hosted

Linux
OS X
Solaris
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

JSON types

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

All properties auto-indexed by default

yes

SQL

Support of SQL

yes

SQL-like query language

yes

APIs and other access methods

Cypher Query Language
JDBC

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

JDBC
Native Spark Datasource
ODBC

RESTful HTTP API

Supported programming languages

C
Java
JavaScript
Python

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

JavaScript

Server-side scripts

Stored procedures

yes

JavaScript

yes

Java

yes

Triggers

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

Implicit feature of the cloud service

Shared Nothhing Auto-Sharding, Columnar Partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Implicit feature of the cloud service

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

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

yes

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