DBMS > AnzoGraph DB vs. Dgraph vs. Dolt vs. LeanXcale

System Properties Comparison AnzoGraph DB vs. Dgraph vs. Dolt vs. LeanXcale

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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

Distributed and scalable native Graph DBMS

A MySQL compatible DBMS with Git-like versioning of data and schema

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

Primary database model

Graph DBMS
RDF store

Graph DBMS

Relational DBMS

Key-value store
Relational DBMS

Secondary database models

Document store

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

Score	0.29
Rank	#303	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	1.53
Rank	#152	Overall
	#15	Graph DBMS

Score	1.02
Rank	#191	Overall
	#89	Relational DBMS

Score	0.36
Rank	#280	Overall
	#40	Key-value stores
	#129	Relational DBMS

Website

cambridgesemantics.com/anzograph

dgraph.io

github.com/dolthub/dolt
www.dolthub.com

www.leanxcale.com

Technical documentation

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

dgraph.io/docs

docs.dolthub.com

Developer

Cambridge Semantics

Dgraph Labs, Inc.

DoltHub Inc

LeanXcale

Initial release

2018

2016

2018

2015

Current release

2.3, January 2021

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache 2.0

Open Source

Apache Version 2.0

commercial

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

Server operating systems

Linux

Linux
OS X
Windows

Linux
macOS
Windows

Data scheme

Schema-free and OWL/RDFS-schema support

schema-free

yes

Typing

predefined data types such as float or date

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

SQL

Support of SQL

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

yes

through Apache Derby

APIs and other access methods

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

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

CLI Client
HTTP REST

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

Supported programming languages

C++
Java
Python

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

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

C
Java
Scala

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

currently in alpha release

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Synchronous replication via Raft

A database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

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

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

Planned for future releases

Only one user is configurable, and must be specified in the config file at startup

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More resources

Recent citations in the news

AnzoGraph review: A graph database for deep analytics
15 April 2019, InfoWorld

AnzoGraph: A W3C Standards-Based Graph Database | by Jo Stichbury
8 February 2019, Towards Data Science

Cambridge Semantics Fits AnzoGraph DB with More Speed, Free Access
23 January 2020, Solutions Review

Back to the future: Does graph database success hang on query language?
5 March 2018, ZDNet

Comparing Graph Databases II. Part 2: ArangoDB, OrientDB, and… | by Sam Bell
20 September 2019, Towards Data Science

provided by Google News

Dgraph on AWS: Setting up a horizontally scalable graph database | Amazon Web Services
1 September 2020, AWS Blog

Dgraph Raises $6M in Seed Funding
20 July 2022, FinSMEs

Dgraph Rises to the Top Graph Database on GitHub With 11 G2 Badges and 11M Downloads
26 May 2021, Business Wire

Dgraph raises $11.5 million for scalable graph database solutions
31 July 2019, VentureBeat

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10 February 2023, InfoQ.com

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