DBMS > Amazon Redshift vs. AnzoGraph DB vs. Google Cloud Spanner vs. Graphite

System Properties Comparison Amazon Redshift vs. AnzoGraph DB vs. Google Cloud Spanner vs. Graphite

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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 horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

Primary database model

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	2.89
Rank	#103	Overall
	#52	Relational DBMS

Score	4.57
Rank	#73	Overall
	#5	Time Series DBMS

Website

aws.amazon.com/redshift

cambridgesemantics.com/anzograph

cloud.google.com/spanner

github.com/graphite-project/graphite-web

Technical documentation

docs.aws.amazon.com/redshift

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

cloud.google.com/spanner/docs

graphite.readthedocs.io

Developer

Amazon (based on PostgreSQL)

Cambridge Semantics

Google

Chris Davis

Initial release

2012

2018

2017

2006

Current release

2.3, January 2021

License

Commercial or Open Source

commercial

free trial version available

commercial

Open Source

Apache 2.0

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
Unix

Data scheme

yes

Schema-free and OWL/RDFS-schema support

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

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

yes

Query statements complying to ANSI 2011

APIs and other access methods

JDBC
ODBC

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

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

HTTP API
Sockets

Supported programming languages

All languages supporting JDBC/ODBC

C++
Java
Python

Go
Java
JavaScript (Node.js)
Python

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions and aggregates

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic sharding

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication in MPP-Cluster

Multi-source replication with 3 replicas for regional instances.

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in MPP-Cluster

Immediate Consistency

none

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

not needed in graphs

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

Transaction concepts

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

ACID

Strict serializable isolation

Concurrency

Support for concurrent manipulation of data

yes

locking

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

Access rights for users and roles

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

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