DBMS > AnzoGraph DB vs. ClickHouse vs. Dgraph vs. Memcached vs. Trafodion

System Properties Comparison AnzoGraph DB vs. ClickHouse vs. Dgraph vs. Memcached vs. Trafodion

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. 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

A high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.

Distributed and scalable native Graph DBMS

In-memory key-value store, originally intended for caching

Transactional SQL-on-Hadoop DBMS

Primary database model

Secondary database models

Time Series 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	15.55
Rank	#38	Overall
	#23	Relational DBMS

Score	1.53
Rank	#152	Overall
	#15	Graph DBMS

Score	18.08
Rank	#32	Overall
	#4	Key-value stores

Website

cambridgesemantics.com/anzograph

Technical documentation

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

clickhouse.com/docs

dgraph.io/docs

github.com/memcached/memcached/wiki

trafodion.apache.org/documentation.html

Developer

Cambridge Semantics

Clickhouse Inc.

Dgraph Labs, Inc.

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Apache Software Foundation, originally developed by HP

Initial release

2018

2016

2003

2014

Current release

2.3, January 2021

v24.4.1.2088-stable, May 2024

1.6.27, May 2024

2.3.0, February 2019

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

BSD license

Open Source

Apache 2.0

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.

Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.
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Implementation language

C++

C++, Java

Server operating systems

Linux

FreeBSD
Linux
macOS

Linux
OS X
Windows

FreeBSD
Linux
OS X
Unix
Windows

Linux

Data scheme

Schema-free and OWL/RDFS-schema support

yes

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.

Close to ANSI SQL (SQL/JSON + extensions)

yes

APIs and other access methods

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

gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

Proprietary protocol

ADO.NET
JDBC
ODBC

Supported programming languages

C++
Java
Python

3rd party library
C++
Elixir

3rd party library
Go

3rd party library
Java

3rd party library
JavaScript (Node.js)

3rd party library
Kotlin

3rd party library
Nim

3rd party library
Perl

3rd party library
PHP

3rd party library
Python

3rd party library
R

3rd party library
Ruby

3rd party library
Rust
Scala

3rd party library

C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

Java Stored Procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

key based and custom

yes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.

Synchronous replication via Raft

none

Repcached, a Memcached patch, provides this functionallity

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

yes

via user defined functions and HBase

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

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

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

Access rights for users and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

Planned for future releases

yes

using SASL (Simple Authentication and Security Layer) protocol

fine grained access rights according to SQL-standard

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