DBMS > CockroachDB vs. Microsoft SQL Server vs. OrigoDB vs. TimescaleDB

System Properties Comparison CockroachDB vs. Microsoft SQL Server vs. OrigoDB vs. TimescaleDB

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Editorial information provided by DB-Engines

Name

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.

Microsofts flagship relational DBMS

A fully ACID in-memory object graph database

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Relational DBMS

Document store
Object oriented DBMS

Time Series DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Relational DBMS

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

Score	6.15
Rank	#55	Overall
	#33	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Website

www.cockroachlabs.com

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

origodb.com

www.timescale.com

Technical documentation

www.cockroachlabs.com/docs

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

origodb.com/docs

docs.timescale.com

Developer

Cockroach Labs

Microsoft

Robert Friberg et al

Timescale

Initial release

2015

1989

2009

under the name LiveDB

2017

Current release

23.1.1, May 2023

SQL Server 2022, November 2022

2.13.0, November 2023

License

Commercial or Open Source

Open Source

Apache 2.0, commercial license available

commercial

restricted free version is available

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Server operating systems

Linux
macOS
Windows

Linux
Windows

Linux
OS X
Windows

Data scheme

dynamic schema

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

can be achieved using .NET

yes

Secondary indexes

yes

SQL

Support of SQL

yes, wire compatible with PostgreSQL

yes

full PostgreSQL SQL syntax

APIs and other access methods

JDBC

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

.NET Client API
HTTP API
LINQ

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

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

.Net

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

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

yes

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

Domain Events

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

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

horizontal partitioning

client side managed; servers are not synchronized

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using RAFT

yes, but depending on the SQL-Server Edition

Source-replica replication

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

depending on model

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

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

fine grained access rights according to SQL-standard

Role based authorization

fine grained access rights according to SQL-standard

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