DBMS > AnzoGraph DB vs. Apache Drill vs. Realm

System Properties Comparison AnzoGraph DB vs. Apache Drill vs. Realm

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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

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Primary database model

Graph DBMS
RDF store

Document store
Relational DBMS

Document store

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

Score	0.23
Rank	#302	Overall
	#26	Graph DBMS
	#14	RDF stores

Score	1.82
Rank	#128	Overall
	#24	Document stores
	#60	Relational DBMS

Score	7.12
Rank	#48	Overall
	#8	Document stores

Website

cambridgesemantics.com/anzograph

drill.apache.org

realm.io

Technical documentation

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

drill.apache.org/docs

realm.io/docs

Developer

Cambridge Semantics

Apache Software Foundation

Realm, acquired by MongoDB in May 2019

Initial release

2018

2012

2014

Current release

2.3, January 2021

1.20.3, January 2023

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache Version 2

Open Source

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.

Server operating systems

Linux

Linux
OS X
Windows

Android
Backend: server-less
iOS
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.

SQL SELECT statement is SQL:2003 compliant

APIs and other access methods

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

JDBC
ODBC
RESTful HTTP API

Supported programming languages

C++
Java
Python

C++

.Net
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

user defined functions and aggregates

user defined functions

runs within the applications so server-side scripts are unnecessary

Triggers

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

none

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

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

Depending on the underlying data source

yes

In-memory capabilities

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

yes

Depending on the underlying data source

yes

In-Memory realm

User concepts

Access control

Access rights for users and roles

Depending on the underlying data source

yes

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Recent citations in the news

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

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

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

Knowledge graph evolution: Platforms that speak your language
30 January 2020, ZDNet

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

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9 June 2016, TheServerSide.com

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