DBMS > Amazon Redshift vs. AnzoGraph DB vs. Graph Engine vs. OpenTSDB vs. TerarkDB

System Properties Comparison Amazon Redshift vs. AnzoGraph DB vs. Graph Engine vs. OpenTSDB vs. TerarkDB

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Scalable Time Series DBMS based on HBase

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

Relational DBMS

Graph DBMS
RDF store

Graph DBMS
Key-value store

Time Series DBMS

Key-value store

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

Score	19.03
Rank	#34	Overall
	#21	Relational DBMS

Score	0.27
Rank	#302	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	0.62
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	1.73
Rank	#147	Overall
	#12	Time Series DBMS

Score	0.04
Rank	#377	Overall
	#58	Key-value stores

Website

aws.amazon.com/redshift

cambridgesemantics.com/anzograph

www.graphengine.io

opentsdb.net

github.com/bytedance/terarkdb

Technical documentation

docs.aws.amazon.com/redshift

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

www.graphengine.io/docs/manual

opentsdb.net/docs/build/html/index.html

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Amazon (based on PostgreSQL)

Cambridge Semantics

Microsoft

currently maintained by Yahoo and other contributors

ByteDance, originally Terark

Initial release

2012

2018

2010

2011

2016

Current release

2.3, January 2021

License

Commercial or Open Source

commercial

free trial version available

Open Source

MIT License

Open Source

LGPL

commercial

restricted open source version available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

.NET and C

Java

C++

Server operating systems

hosted

Linux

.NET

Linux
Windows

Data scheme

yes

Schema-free and OWL/RDFS-schema support

yes

schema-free

Typing

predefined data types such as float or date

yes

numeric data for metrics, strings for tags

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

restricted

SQL

Support of SQL

yes

does not fully support an SQL-standard

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

APIs and other access methods

JDBC
ODBC

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

RESTful HTTP API

HTTP API
Telnet API

C++ API
Java API

Supported programming languages

All languages supporting JDBC/ODBC

C++
Java
Python

C#
C++
F#
Visual Basic

Erlang
Go
Java
Python
R
Ruby

C++
Java

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions and aggregates

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic sharding

horizontal partitioning

Sharding

based on HBase

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication in MPP-Cluster

selectable replication factor

based on HBase

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

Immediate Consistency in MPP-Cluster

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

not needed in graphs

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

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

fine grained access rights according to SQL-standard

Access rights for users and roles

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