DBMS > CockroachDB vs. Graph Engine vs. JaguarDB vs. Microsoft SQL Server vs. Netezza

System Properties Comparison CockroachDB vs. Graph Engine vs. JaguarDB vs. Microsoft SQL Server vs. Netezza

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.

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Performant, highly scalable DBMS for AI and IoT applications

Microsofts flagship relational DBMS

Data warehouse and analytics appliance part of IBM PureSystems

Primary database model

Relational DBMS

Graph DBMS
Key-value store

Key-value store
Vector DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	6.15
Rank	#55	Overall
	#33	Relational DBMS

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Website

www.cockroachlabs.com

www.graphengine.io

www.jaguardb.com

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

www.ibm.com/products/netezza

Technical documentation

www.cockroachlabs.com/docs

www.graphengine.io/docs/manual

www.jaguardb.com/support.html

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

Developer

Cockroach Labs

Microsoft

DataJaguar, Inc.

Microsoft

IBM

Initial release

2015

2010

2015

1989

2000

Current release

23.1.1, May 2023

3.3 July 2023

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

Apache 2.0, commercial license available

Open Source

MIT License

Open Source

GPL V3.0

commercial

restricted free version is available

commercial

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

.NET and C

C++

the server part. Clients available in other languages

C++

Server operating systems

Linux
macOS
Windows

.NET

Linux

Linux
Windows

Linux

included in appliance

Data scheme

dynamic schema

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

yes, wire compatible with PostgreSQL

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

APIs and other access methods

JDBC

RESTful HTTP API

JDBC
ODBC

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

JDBC
ODBC
OLE DB

Supported programming languages

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

C#
C++
F#
Visual Basic

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

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

C
C++
Fortran
Java
Lua
Perl
Python
R

Server-side scripts

Stored procedures

yes

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

yes

Triggers

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

horizontal partitioning

Sharding

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using RAFT

Multi-source replication

yes, but depending on the SQL-Server Edition

Source-replica replication

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

Foreign keys

Referential integrity

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

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

rights management via user accounts

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

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