DBMS > Amazon Redshift vs. AnzoGraph DB vs. BigchainDB vs. Microsoft Azure Cosmos DB vs. Teradata Aster

System Properties Comparison Amazon Redshift vs. AnzoGraph DB vs. BigchainDB vs. Microsoft Azure Cosmos DB vs. Teradata Aster

Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

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

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

Globally distributed, horizontally scalable, multi-model database service

Platform for big data analytics on multistructured data sources and types

Primary database model

Relational DBMS

Graph DBMS
RDF store

Document store

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

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

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Website

aws.amazon.com/redshift

cambridgesemantics.com/anzograph

www.bigchaindb.com

azure.microsoft.com/services/cosmos-db

Technical documentation

docs.aws.amazon.com/redshift

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

bigchaindb.readthedocs.io/en/latest

learn.microsoft.com/azure/cosmos-db

Developer

Amazon (based on PostgreSQL)

Cambridge Semantics

Microsoft

Teradata

Initial release

2012

2018

2016

2014

2005

Current release

2.3, January 2021

License

Commercial or Open Source

commercial

free trial version available

Open Source

AGPL v3

commercial

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

Python

Server operating systems

hosted

Linux

hosted

Linux

Data scheme

yes

Schema-free and OWL/RDFS-schema support

schema-free

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

Typing

predefined data types such as float or date

yes

JSON types

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.

yes

in Aster File Store

Secondary indexes

restricted

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

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

SQL-like query language

yes

APIs and other access methods

JDBC
ODBC

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

CLI Client
RESTful HTTP API

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

All languages supporting JDBC/ODBC

C++
Java
Python

Go
Haskell
Java
JavaScript
Python
Ruby

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions and aggregates

JavaScript

R packages

Triggers

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic sharding

Sharding

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication in MPP-Cluster

selectable replication factor

yes

Implicit feature of the cloud service

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in MPP-Cluster

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes,with MongoDB ord RethinkDB

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

yes

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

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