DBMS > AnzoGraph DB vs. EsgynDB vs. Realm vs. Tarantool vs. ToroDB

System Properties Comparison AnzoGraph DB vs. EsgynDB vs. Realm vs. Tarantool vs. ToroDB

Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

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

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

In-memory computing platform with a flexible data schema for efficiently building high-performance applications

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Graph DBMS
RDF store

Relational DBMS

Document store

Document store
Key-value store
Relational DBMS

Document store

Secondary database models

Spatial DBMS

with Tarantool/GIS extension

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	0.15
Rank	#325	Overall
	#144	Relational DBMS

Score	7.18
Rank	#52	Overall
	#8	Document stores

Score	1.63
Rank	#139	Overall
	#25	Document stores
	#24	Key-value stores
	#65	Relational DBMS

Website

cambridgesemantics.com/anzograph

www.esgyn.cn

realm.io

www.tarantool.io

github.com/torodb/server

Technical documentation

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

realm.io/docs

www.tarantool.io/en/doc

Developer

Cambridge Semantics

Esgyn

Realm, acquired by MongoDB in May 2019

8Kdata

Initial release

2018

2015

2014

2008

2016

Current release

2.3, January 2021

2.10.0, May 2022

License

Commercial or Open Source

commercial

free trial version available

commercial

Open Source

BSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise

Open Source

AGPL-V3

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++, Java

C and C++

Java

Server operating systems

Linux

Android
Backend: server-less
iOS
Windows

BSD
Linux
macOS

All OS with a Java 7 VM

Data scheme

Schema-free and OWL/RDFS-schema support

yes

Flexible data schema: relational definition for tables with ability to store json-like documents in columns

schema-free

Typing

predefined data types such as float or date

yes

string, double, decimal, uuid, integer, blob, boolean, datetime

yes

string, integer, double, boolean, date, object_id

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

Full-featured ANSI SQL support

APIs and other access methods

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

ADO.NET
JDBC
ODBC

Open binary protocol

Supported programming languages

C++
Java
Python

All languages supporting JDBC/ODBC/ADO.Net

.Net
Java

with Android only
Objective-C
React Native
Swift

C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust

Server-side scripts

Stored procedures

user defined functions and aggregates

Java Stored Procedures

runs within the applications so server-side scripts are unnecessary

Lua, C and SQL stored procedures

Triggers

yes

Change Listeners

yes, before/after data modification events, on replication events, client session events

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

none

Sharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Multi-source replication between multi datacenters

none

Asynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)

Source-replica replication

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

Immediate Consistency

Casual consistency across sharding partitions
Eventual consistency within replicaset partition

when using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition

when using Raft

Eventual Consistency
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

ACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions

Concurrency

Support for concurrent manipulation of data

yes

yes, cooperative multitasking

yes

Durability

Support for making data persistent

yes

yes, write ahead logging

yes

In-memory capabilities

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

yes

In-Memory realm

yes, full featured in-memory storage engine with persistence

User concepts

Access control

Access rights for users and roles

fine grained access rights according to SQL-standard

yes

Access Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

Access rights for users and roles

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More resources

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