DBMS > AnzoGraph DB vs. Apache Impala vs. CouchDB vs. JanusGraph vs. LeanXcale

System Properties Comparison AnzoGraph DB vs. Apache Impala vs. CouchDB vs. JanusGraph vs. LeanXcale

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

Analytic DBMS for Hadoop

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

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

Primary database model

Key-value store
Relational DBMS

Secondary database models

Document store

Spatial DBMS

using the Geocouch extension

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	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	8.30
Rank	#47	Overall
	#7	Document stores

Score	2.02
Rank	#125	Overall
	#12	Graph DBMS

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

Website

cambridgesemantics.com/anzograph

Technical documentation

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

impala.apache.org/impala-docs.html

docs.couchdb.org/en/stable

docs.janusgraph.org

Developer

Cambridge Semantics

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

Linux Foundation; originally developed as Titan by Aurelius

LeanXcale

Initial release

2018

2013

2005

2017

2015

Current release

2.3, January 2021

4.1.0, June 2022

3.3.3, December 2023

0.6.3, February 2023

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache Version 2

Open Source

Apache version 2

Open Source

Apache 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

C++

Erlang

Java

Server operating systems

Linux

Android
BSD
Linux
OS X
Solaris
Windows

Linux
OS X
Unix
Windows

Data scheme

Schema-free and OWL/RDFS-schema support

yes

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

via views

yes

SQL

Support of SQL

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

SQL-like DML and DDL statements

yes

through Apache Derby

APIs and other access methods

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

JDBC
ODBC

RESTful HTTP/JSON API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

Supported programming languages

C++
Java
Python

All languages supporting JDBC/ODBC

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

Clojure
Java
Python

C
Java
Scala

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

user defined functions and integration of map-reduce

View functions in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

improved architecture with release 2.0

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

selectable replication factor

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

yes

query execution via MapReduce

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Eventual Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

atomic operations within a single document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Access rights for users can be defined per database

User authentification and security via Rexster Graph Server

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