DBMS > AnzoGraph DB vs. DolphinDB vs. Drizzle vs. Neo4j vs. RocksDB

System Properties Comparison AnzoGraph DB vs. DolphinDB vs. Drizzle vs. Neo4j vs. RocksDB

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

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

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

Scalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offerings

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Secondary database models

Relational DBMS

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	4.03
Rank	#78	Overall
	#6	Time Series DBMS

Score	44.89
Rank	#21	Overall
	#1	Graph DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

cambridgesemantics.com/anzograph

www.dolphindb.com

neo4j.com

rocksdb.org

Technical documentation

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

docs.dolphindb.cn/en/help200/index.html

neo4j.com/docs

github.com/facebook/rocksdb/wiki

Developer

Cambridge Semantics

DolphinDB, Inc

Drizzle project, originally started by Brian Aker

Neo4j, Inc.

Facebook, Inc.

Initial release

2018

2008

2007

2013

Current release

2.3, January 2021

v2.00.4, January 2022

7.2.4, September 2012

5.20, May 2024

9.2.1, May 2024

License

Commercial or Open Source

commercial

free trial version available

commercial

free community version available

Open Source

GNU GPL

Open Source

GPL version3, commercial licenses available

Open Source

BSD

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.

Neo4j Aura: Neo4j’s fully managed cloud service: The zero-admin, always-on graph database for cloud developers.

Implementation language

C++

Java, Scala

C++

Server operating systems

Linux

Linux
Windows

FreeBSD
Linux
OS X

Linux

Can also be used server-less as embedded Java database.
OS X
Solaris
Windows

Linux

Data scheme

Schema-free and OWL/RDFS-schema support

yes

schema-free and schema-optional

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

pluggable indexing subsystem, by default Apache Lucene

SQL

Support of SQL

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

SQL-like query language

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
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

JDBC

Bolt protocol
Cypher query language
Java API
Neo4j-OGM

Object Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3

C++ API
Java API

Supported programming languages

C++
Java
Python

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

C
C++
Java
PHP

.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

User defined Procedures and Functions

Triggers

hooks for callbacks inside the server can be used.

yes

via event handler

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

horizontal partitioning

Sharding

yes using Neo4j Fabric

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

yes

Multi-source replication
Source-replica replication

Causal Clustering using Raft protocol

available in in Enterprise Version only

yes

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

Causal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode

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

yes

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

Administrators, Users, Groups

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Users, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)

More information provided by the system vendor

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Key customers

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Market metrics

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Licensing and pricing models

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