DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. AnzoGraph DB vs. CockroachDB vs. Google BigQuery vs. SAP SQL Anywhere

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. AnzoGraph DB vs. CockroachDB vs. Google BigQuery vs. SAP SQL Anywhere

Editorial information provided by DB-Engines

Name

Description

An online MPP (Massively Parallel Processing) data warehousing service based on Greenplum

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

CockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.

Large scale data warehouse service with append-only tables

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Primary database model

Relational DBMS

Graph DBMS
RDF store

Relational DBMS

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

Score	0.68
Rank	#231	Overall
	#105	Relational DBMS

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

Score	6.15
Rank	#55	Overall
	#33	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Website

www.alibabacloud.com/product/hybriddb-postgresql

cambridgesemantics.com/anzograph

www.cockroachlabs.com

cloud.google.com/bigquery

www.sap.com/products/technology-platform/sql-anywhere.html

Technical documentation

www.alibabacloud.com/help/en/analyticdb-for-postgresql/latest/product-introduction-overview

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

www.cockroachlabs.com/docs

cloud.google.com/bigquery/docs

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Cambridge Semantics

Cockroach Labs

Google

SAP

formerly Sybase

Initial release

2016

2018

2015

2010

1992

Current release

2.3, January 2021

23.1.1, May 2023

17, July 2015

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache 2.0, commercial license available

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

Server operating systems

hosted

Linux

Linux
macOS
Windows

hosted

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

yes

Schema-free and OWL/RDFS-schema support

dynamic schema

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

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

yes, wire compatible with PostgreSQL

yes

APIs and other access methods

JDBC
ODBC

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

JDBC

RESTful HTTP/JSON API

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

C
Java
Perl
Python
R

C++
Java
Python

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

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

yes

user defined functions and aggregates

user defined functions

in JavaScript

yes, in C/C++, Java, .Net or Perl

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Automatic sharding

horizontal partitioning (by key range)

all tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFT

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Multi-source replication in MPP-Cluster

Multi-source replication using RAFT

Source-replica replication

Database mirroring

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

Foreign keys

Referential integrity

yes

not needed in graphs

yes

Transaction concepts

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

ACID

Since BigQuery is designed for querying 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

fine grained access rights according to SQL-standard

Access rights for users and roles

Role-based access control

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

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