DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. CockroachDB vs. Google BigQuery vs. Hawkular Metrics vs. Infobright

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. CockroachDB vs. Google BigQuery vs. Hawkular Metrics vs. Infobright

Editorial information provided by DB-Engines

Name

Description

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

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

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

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

Score	0.68
Rank	#231	Overall
	#105	Relational DBMS

Score	6.15
Rank	#55	Overall
	#33	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	0.96
Rank	#194	Overall
	#91	Relational DBMS

Website

www.alibabacloud.com/product/hybriddb-postgresql

www.cockroachlabs.com

cloud.google.com/bigquery

www.hawkular.org

ignitetech.com/softwarelibrary/infobrightdb

Technical documentation

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

www.cockroachlabs.com/docs

cloud.google.com/bigquery/docs

www.hawkular.org/hawkular-metrics/docs/user-guide

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Cockroach Labs

Google

Community supported by Red Hat

Ignite Technologies Inc.; formerly InfoBright Inc.

Initial release

2016

2015

2010

2014

2005

Current release

23.1.1, May 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0, commercial license available

commercial

Open Source

Apache 2.0

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

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

Java

Server operating systems

hosted

Linux
macOS
Windows

hosted

Linux
OS X
Windows

Linux
Windows

Data scheme

yes

dynamic schema

yes

schema-free

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

Knowledge Grid Technology used instead

SQL

Support of SQL

yes

yes, wire compatible with PostgreSQL

yes

APIs and other access methods

JDBC
ODBC

JDBC

RESTful HTTP/JSON API

HTTP REST

ADO.NET
JDBC
ODBC

Supported programming languages

C
Java
Perl
Python
R

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

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Go
Java
Python
Ruby

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

user defined functions

in JavaScript

Triggers

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

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

Sharding

based on Cassandra

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Multi-source replication using RAFT

selectable replication factor

based on Cassandra

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

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

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

exploiting MySQL or PostgreSQL frontend capabilities

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