DBMS > AnzoGraph DB vs. ArcadeDB vs. Drizzle vs. LevelDB vs. TerarkDB

System Properties Comparison AnzoGraph DB vs. ArcadeDB vs. Drizzle vs. LevelDB vs. TerarkDB

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle 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

Fast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewritten

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Graph DBMS
RDF store

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Relational DBMS

Key-value store

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

Score	0.23
Rank	#307	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	0.02
Rank	#366	Overall
	#50	Document stores
	#38	Graph DBMS
	#53	Key-value stores
	#36	Time Series DBMS

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

cambridgesemantics.com/anzograph

arcadedb.com

github.com/google/leveldb

github.com/bytedance/terarkdb

Technical documentation

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

docs.arcadedb.com

github.com/google/leveldb/blob/main/doc/index.md

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Cambridge Semantics

Arcade Data

Drizzle project, originally started by Brian Aker

Google

ByteDance, originally Terark

Initial release

2018

2021

2008

2011

2016

Current release

2.3, January 2021

September 2021

7.2.4, September 2012

1.23, February 2021

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache Version 2.0

Open Source

GNU GPL

Open Source

BSD

commercial

restricted open source version available

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

Java

C++

Server operating systems

Linux

All OS with a Java VM

FreeBSD
Linux
OS X

Illumos
Linux
OS X
Windows

Data scheme

Schema-free and OWL/RDFS-schema support

schema-free

yes

schema-free

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-like query language, no joins

yes

with proprietary extensions

APIs and other access methods

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

JDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin

JDBC

C++ API
Java API

Supported programming languages

C++
Java
Python

Java

C
C++
Java
PHP

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

C++
Java

Server-side scripts

Stored procedures

user defined functions and aggregates

Triggers

hooks for callbacks inside the server can be used.

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

Source-replica replication

Multi-source replication
Source-replica replication

none

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

relationship 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

with automatic compression on writes

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

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