DBMS > CockroachDB vs. FatDB vs. Microsoft Azure Cosmos DB vs. Microsoft Azure Table Storage vs. OpenTSDB

System Properties Comparison CockroachDB vs. FatDB vs. Microsoft Azure Cosmos DB vs. Microsoft Azure Table Storage 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

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.

Globally distributed, horizontally scalable, multi-model database service

A Wide Column Store for rapid development using massive semi-structured datasets

Scalable Time Series DBMS based on HBase

Primary database model

Relational DBMS

Document store
Key-value store

Document store
Graph DBMS
Key-value store
Wide column store

Wide column store

Time Series DBMS

Secondary database models

Spatial DBMS

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

Score	6.15
Rank	#55	Overall
	#33	Relational DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Score	1.68
Rank	#146	Overall
	#12	Time Series DBMS

Website

www.cockroachlabs.com

azure.microsoft.com/services/cosmos-db

azure.microsoft.com/en-us/services/storage/tables

opentsdb.net

Technical documentation

www.cockroachlabs.com/docs

learn.microsoft.com/azure/cosmos-db

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

Developer

Cockroach Labs

FatCloud

Microsoft

currently maintained by Yahoo and other contributors

Initial release

2015

2012

2014

2012

2011

Current release

23.1.1, May 2023

License

Commercial or Open Source

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

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Implementation language

Java

Server operating systems

Linux
macOS
Windows

Windows

hosted

Linux
Windows

Data scheme

dynamic schema

schema-free

Typing

predefined data types such as float or date

yes

JSON types

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.

Secondary indexes

yes

All properties auto-indexed by default

SQL

Support of SQL

yes, wire compatible with PostgreSQL

Via inetgration in SQL Server

SQL-like query language

APIs and other access methods

JDBC

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

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

RESTful HTTP API

HTTP API
Telnet API

Supported programming languages

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

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

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

Erlang
Go
Java
Python
R
Ruby

Server-side scripts

Stored procedures

yes

via applications

JavaScript

Triggers

yes

via applications

JavaScript

Partitioning methods

Methods for storing different data on different nodes

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

Implicit feature of the cloud service

Sharding

Implicit feature of the cloud service

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using RAFT

selectable replication factor

yes

Implicit feature of the cloud service

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session 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

Multi-item ACID transactions with snapshot isolation within a partition

optimistic locking

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

Role-based access control

Can implement custom security layer via applications

Access rights can be defined down to the item level

Access rights based on private key authentication or shared access signatures

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