DBMS > Alibaba Cloud Table Store vs. BigObject vs. CockroachDB vs. FatDB vs. Microsoft SQL Server

System Properties Comparison Alibaba Cloud Table Store vs. BigObject vs. CockroachDB vs. FatDB vs. Microsoft SQL Server

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

A fully managed Wide Column Store for large quantities of semi-structured data with real-time access

Analytic DBMS for real-time computations and queries

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.

Microsofts flagship relational DBMS

Primary database model

Wide column store

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Document store
Key-value store

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.31
Rank	#297	Overall
	#11	Wide column stores

Score	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	5.73
Rank	#58	Overall
	#34	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Website

www.alibabacloud.com/product/table-store

bigobject.io

www.cockroachlabs.com

www.microsoft.com/en-us/sql-server

Technical documentation

www.alibabacloud.com/help/en/tablestore

docs.bigobject.io

www.cockroachlabs.com/docs

learn.microsoft.com/en-US/sql/sql-server

Developer

Alibaba

BigObject, Inc.

Cockroach Labs

FatCloud

Microsoft

Initial release

2016

2015

2012

1989

Current release

24.1.0, May 2024

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache 2.0, commercial license available

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Server operating systems

hosted

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux
macOS
Windows

Windows

Linux
Windows

Data scheme

schema-free

yes

dynamic schema

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

SQL

Support of SQL

SQL-like DML and DDL statements

yes, wire compatible with PostgreSQL

Via inetgration in SQL Server

yes

APIs and other access methods

HTTP API

fluentd
ODBC
RESTful HTTP API

JDBC

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

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Supported programming languages

Java
Python

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

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Server-side scripts

Stored procedures

Lua

yes

via applications

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

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

tables can be distributed across several files (horizontal partitioning); sharding through federation

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

none

Multi-source replication using RAFT

selectable replication factor

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

Atomic single-row operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

Access rights based on subaccounts and tokens

Role-based access control

Can implement custom security layer via applications

fine grained access rights according to SQL-standard

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