DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. CockroachDB vs. FatDB vs. Google BigQuery vs. OpenTSDB

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. CockroachDB vs. FatDB vs. Google BigQuery vs. OpenTSDB

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

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.

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Large scale data warehouse service with append-only tables

Scalable Time Series DBMS based on HBase

Primary database model

Relational DBMS

Document store
Key-value store

Relational DBMS

Time Series 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	1.68
Rank	#146	Overall
	#12	Time Series DBMS

Website

www.alibabacloud.com/product/hybriddb-postgresql

www.cockroachlabs.com

cloud.google.com/bigquery

opentsdb.net

Technical documentation

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

www.cockroachlabs.com/docs

cloud.google.com/bigquery/docs

opentsdb.net/docs/build/html/index.html

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Cockroach Labs

FatCloud

Google

currently maintained by Yahoo and other contributors

Initial release

2016

2015

2012

2010

2011

Current release

24.1.0, May 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0, commercial license available

commercial

Open Source

LGPL

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

Windows

hosted

Linux
Windows

Data scheme

yes

dynamic schema

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

numeric data for metrics, strings for tags

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

yes, wire compatible with PostgreSQL

Via inetgration in SQL Server

yes

APIs and other access methods

JDBC
ODBC

JDBC

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

RESTful HTTP/JSON API

HTTP API
Telnet API

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

Erlang
Go
Java
Python
R
Ruby

Server-side scripts

Stored procedures

yes

via applications

user defined functions

in JavaScript

Triggers

yes

via applications

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

Sharding

none

Sharding

based on HBase

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 HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

based on HBase

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

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.

User concepts

Access control

fine grained access rights according to SQL-standard

Role-based access control

Can implement custom security layer via applications

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

Google Cloud Identity & Access Management (IAM)

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