DBMS > AnzoGraph DB vs. BigchainDB vs. NCache vs. SQLite vs. TinkerGraph

System Properties Comparison AnzoGraph DB vs. BigchainDB vs. NCache vs. SQLite vs. TinkerGraph

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

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

Open-Source and Enterprise in-memory Key-Value Store

Widely used embeddable, in-process RDBMS

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

Primary database model

Secondary database models

Document store
Search engine

Using distributed Lucene

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	0.85
Rank	#208	Overall
	#35	Document stores

Score	0.96
Rank	#195	Overall
	#29	Key-value stores

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	0.13
Rank	#345	Overall
	#35	Graph DBMS

Website

cambridgesemantics.com/anzograph

www.bigchaindb.com

www.alachisoft.com/ncache

www.sqlite.org

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

Technical documentation

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

bigchaindb.readthedocs.io/en/latest

www.alachisoft.com/resources/docs

www.sqlite.org/docs.html

Developer

Cambridge Semantics

Alachisoft

Dwayne Richard Hipp

Initial release

2018

2016

2005

2000

2009

Current release

2.3, January 2021

5.3.3, April 2024

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

free trial version available

Open Source

AGPL v3

Open Source

Enterprise Edition available

Open Source

Public Domain

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Python

C#, .NET, .NET Core, Java

Java

Server operating systems

Linux

Linux
Windows

server-less

Data scheme

Schema-free and OWL/RDFS-schema support

schema-free

yes

dynamic column types

schema-free

Typing

predefined data types such as float or date

partial

Supported data types are Lists, Queues, Hashsets, Dictionary and Counter

yes

not rigid because of 'dynamic typing' concept.

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-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.

yes

SQL-92 is not fully supported

APIs and other access methods

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

CLI Client
RESTful HTTP API

IDistributedCache
JCache
LINQ
Proprietary native API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

TinkerPop 3

Supported programming languages

C++
Java
Python

Go
Haskell
Java
JavaScript
Python
Ruby

.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Groovy
Java

Server-side scripts

Stored procedures

user defined functions and aggregates

support for stored procedures with SQL-Server CLR

Triggers

yes

Notifications

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

selectable replication factor

yes, with selectable consistency level

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

Eventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology

none

Foreign keys

Referential integrity

not needed in graphs

yes

Relationships in graphs

Transaction concepts

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

ACID

optimistic locking and pessimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

Durability

Support for making data persistent

yes

yes,with MongoDB ord RethinkDB

yes

optional

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

yes

Authentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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