DBMS > Amazon Redshift vs. Blazegraph vs. Google Cloud Bigtable vs. Graphite vs. Teradata

System Properties Comparison Amazon Redshift vs. Blazegraph vs. Google Cloud Bigtable vs. Graphite vs. Teradata

Editorial information provided by DB-Engines

Name

Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.

Description

Large scale data warehouse service for use with business intelligence tools

High-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Relational DBMS

Graph DBMS
RDF store

Key-value store
Wide column store

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	0.81
Rank	#213	Overall
	#19	Graph DBMS
	#8	RDF stores

Score	3.15
Rank	#95	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	4.83
Rank	#67	Overall
	#4	Time Series DBMS

Score	44.87
Rank	#22	Overall
	#15	Relational DBMS

Website

aws.amazon.com/redshift

blazegraph.com

cloud.google.com/bigtable

github.com/graphite-project/graphite-web

www.teradata.com

Technical documentation

docs.aws.amazon.com/redshift

wiki.blazegraph.com

cloud.google.com/bigtable/docs

graphite.readthedocs.io

docs.teradata.com

Developer

Amazon (based on PostgreSQL)

Blazegraph

Google

Chris Davis

Teradata

Initial release

2012

2006

2015

2006

1984

Current release

2.1.5, March 2019

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

commercial

Open Source

extended commercial license available

commercial

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Python

Server operating systems

hosted

Linux
OS X
Windows

hosted

Linux
Unix

hosted
Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

RDF literal types

Numeric data only

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

Secondary indexes

restricted

yes

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

yes

does not fully support an SQL-standard

SPARQL is used as query language

yes

SQL 2016 + extensions

APIs and other access methods

JDBC
ODBC

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

HTTP API
Sockets

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

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

JavaScript (Node.js)
Python

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

Server-side scripts

Stored procedures

user defined functions

in Python

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Internal replication in Colossus, and regional replication between two clusters in different zones

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

none

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Relationships in Graphs

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Atomic single-row operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

locking

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

fine grained access rights according to SQL-standard

Security and Authentication via Web Application Container (Tomcat, Jetty)

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

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