DBMS > CrateDB vs. eXtremeDB vs. Microsoft Azure SQL Database vs. Microsoft SQL Server

System Properties Comparison CrateDB vs. eXtremeDB vs. Microsoft Azure SQL Database vs. Microsoft SQL Server

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Editorial information provided by DB-Engines

Name

Description

Distributed Database based on Lucene

Natively in-memory DBMS with options for persistency, high-availability and clustering

Database as a Service offering with high compatibility to Microsoft SQL Server

Microsofts flagship relational DBMS

Primary database model

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Relational DBMS
Time Series DBMS

Relational DBMS

Secondary database models

Relational DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	0.64
Rank	#225	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#12	Vector DBMS

Score	0.94
Rank	#189	Overall
	#87	Relational DBMS
	#17	Time Series DBMS

Score	76.53
Rank	#16	Overall
	#11	Relational DBMS

Score	799.81
Rank	#3	Overall
	#3	Relational DBMS

Website

cratedb.com

www.mcobject.com

azure.microsoft.com/en-us/products/azure-sql/database

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

Technical documentation

cratedb.com/docs

www.mcobject.com/docs/extremedb.htm

docs.microsoft.com/en-us/azure/azure-sql

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

Developer

Crate

McObject

Microsoft

Initial release

2013

2001

2010

1989

Current release

5.8.1, August 2024

8.2, 2021

V12

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

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

Java

C and C++

C++

Server operating systems

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

AIX
HP-UX
Linux
macOS
Solaris
Windows

hosted

Linux
Windows

Data scheme

Flexible Schema (defined schema, partial 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.

support of XML interfaces available

yes

Secondary indexes

yes

SQL

Support of SQL

yes, but no triggers and constraints, and PostgreSQL compatibility

yes

with the option: eXtremeSQL

yes

APIs and other access methods

ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API

ADO.NET
JDBC
ODBC

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

Supported programming languages

.NET
Erlang
Go

community maintained client
Java
JavaScript (Node.js)

community maintained client
Perl

community maintained client
PHP
Python
R
Ruby

community maintained client
Scala

community maintained client

.Net
C
C#
C++
Java
Lua
Python
Scala

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

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

Server-side scripts

Stored procedures

user defined functions (Javascript)

yes

Transact SQL

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

Triggers

yes

by defining events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning / sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

Configurable replication on table/partition-level

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

yes, with always 3 replicas available

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Read-after-write consistency on record level

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

unique row identifiers can be used for implementing an optimistic concurrency control strategy

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic (MVCC) and pessimistic (locking) strategies available

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

rights management via user accounts

fine grained access rights according to SQL-standard

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More resources

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Recent citations in the news

CrateDB, a name that we will hear more in the future
24 October 2024, AWS Blog

Crate.io Introduces CrateDB 2.0 Enterprise and Open Source Editions
16 May 2017, Business Wire

CrateDB Announces New Executive Leadership Appointments
29 August 2023, PR Newswire

CrateDB: The IoT and machine data-focused database
14 December 2016, Network World

Crate.io Brings Power of Industrial SQL Time Series to Azure IoT Hub to Reduce IoT Systems Cost and Complexity
24 September 2018, Business Wire

provided by Google News

McObject
17 November 2021, Electronic Design

Latest embedded DBMS supports asymmetric multiprocessing systems
24 May 2023, Embedded

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