DBMS > CockroachDB vs. FatDB vs. Microsoft Azure Table Storage vs. Yaacomo vs. YottaDB

System Properties Comparison CockroachDB vs. FatDB vs. Microsoft Azure Table Storage vs. Yaacomo vs. YottaDB

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.

Yaacomo seems to be discontinued and is removed from the DB-Engines 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.

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

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

A fast and solid embedded Key-value store

Primary database model

Relational DBMS

Document store
Key-value store

Wide column store

Relational DBMS

Key-value store

Secondary database models

Relational DBMS

using the Octo plugin

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

Score	5.73
Rank	#58	Overall
	#34	Relational DBMS

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Score	0.28
Rank	#306	Overall
	#44	Key-value stores

Website

www.cockroachlabs.com

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

yaacomo.com

yottadb.com

Technical documentation

www.cockroachlabs.com/docs

yottadb.com/resources/documentation

Developer

Cockroach Labs

FatCloud

Microsoft

Q2WEB GmbH

YottaDB, LLC

Initial release

2015

2012

2009

2001

Current release

24.1.0, May 2024

License

Commercial or Open Source

Open Source

Apache 2.0, commercial license available

commercial

Open Source

AGPL 3.0

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

Server operating systems

Linux
macOS
Windows

Windows

hosted

Android
Linux
Windows

Docker
Linux

Data scheme

dynamic schema

schema-free

yes

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

yes, wire compatible with PostgreSQL

Via inetgration in SQL Server

yes

by using the Octo plugin

APIs and other access methods

JDBC

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

RESTful HTTP API

JDBC
ODBC

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

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

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

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

yes

via applications

Triggers

yes

via applications

yes

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

horizontal partitioning

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. Replication either local, cross-facility or geo-redundant.

Source-replica replication

yes

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

optimistic locking

ACID

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.

yes

User concepts

Access control

Role-based access control

Can implement custom security layer via applications

Access rights based on private key authentication or shared access signatures

fine grained access rights according to SQL-standard

Users and groups based on OS-security mechanisms

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More resources

Recent citations in the news

Cockroach Labs Deepens Partnership with Google Cloud, CockroachDB Selected to Join Google Distributed Cloud
9 April 2024, PR Newswire

CockroachDB tempts legacy databases to crawl into the cloud age
29 January 2024, The Register

How DoorDash Migrated from Aurora Postgres to CockroachDB
5 December 2023, The New Stack

DoorDash Uses CockroachDB to Create Config Management Platform for Microservices
14 February 2024, InfoQ.com

How to Unlock Real-Time Data Streams with CockroachDB and Amazon MSK | Amazon Web Services
6 November 2023, AWS Blog

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9 July 2021, hackernoon.com

How to use Azure Table storage in .Net
14 January 2019, InfoWorld

Quick Guide to Azure Storage Pricing
16 May 2023, DevOps.com

How to write data to Azure Table Store with an Azure Function
14 April 2017, Experts Exchange

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