DBMS > AnzoGraph DB vs. CockroachDB vs. EsgynDB vs. Microsoft Azure Cosmos DB vs. Vitess

System Properties Comparison AnzoGraph DB vs. CockroachDB vs. EsgynDB vs. Microsoft Azure Cosmos DB vs. Vitess

Editorial information provided by DB-Engines

Name

Description

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

CockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.

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

Globally distributed, horizontally scalable, multi-model database service

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Graph DBMS
RDF store

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

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

Score	0.22
Rank	#302	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	4.74
Rank	#67	Overall
	#36	Relational DBMS

Score	0.15
Rank	#325	Overall
	#144	Relational DBMS

Score	24.97
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.86
Rank	#202	Overall
	#95	Relational DBMS

Website

cambridgesemantics.com/anzograph

www.cockroachlabs.com

www.esgyn.cn

azure.microsoft.com/services/cosmos-db

vitess.io

Technical documentation

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

www.cockroachlabs.com/docs

learn.microsoft.com/azure/cosmos-db

vitess.io/docs

Developer

Cambridge Semantics

Cockroach Labs

Esgyn

Microsoft

The Linux Foundation, PlanetScale

Initial release

2018

2015

2014

2013

Current release

2.3, January 2021

24.1.0, May 2024

15.0.2, December 2022

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache 2.0, commercial license available

commercial

Open Source

Apache Version 2.0, commercial licenses 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

C++, Java

Server operating systems

Linux

Linux
macOS
Windows

Linux

hosted

Docker
Linux
macOS

Data scheme

Schema-free and OWL/RDFS-schema support

dynamic schema

yes

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

SPARQL and SPARQL* as primary query language. Cypher preview.

yes, wire compatible with PostgreSQL

yes

SQL-like query language

yes

with proprietary extensions

APIs and other access methods

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

JDBC

ADO.NET
JDBC
ODBC

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

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

C++
Java
Python

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

All languages supporting JDBC/ODBC/ADO.Net

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

user defined functions and aggregates

Java Stored Procedures

JavaScript

yes

proprietary syntax

Triggers

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

horizontal partitioning (by key range)

all tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFT

Sharding

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Multi-source replication using RAFT

Multi-source replication between multi datacenters

yes

Implicit feature of the cloud service

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

not needed in graphs

yes

not for MyISAM storage engine

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 at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

Access rights for users and roles

Role-based access control

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

Users with fine-grained authorization concept

no user groups or roles

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