DBMS > CrateDB vs. Microsoft SQL Server vs. Prometheus vs. Tigris vs. ToroDB

System Properties Comparison CrateDB vs. Microsoft SQL Server vs. Prometheus vs. Tigris vs. ToroDB

Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Distributed Database based on Lucene

Microsofts flagship relational DBMS

Open-source Time Series DBMS and monitoring system

A horizontally scalable, ACID transactional, document database available both as a fully managed cloud service and for deployment on self-managed infrastructure

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Relational DBMS

Time Series DBMS

Document store
Key-value store
Search engine
Time Series DBMS

Document store

Secondary database models

Relational DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	0.71
Rank	#227	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#10	Vector DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	7.69
Rank	#50	Overall
	#3	Time Series DBMS

Score	0.09
Rank	#363	Overall
	#49	Document stores
	#54	Key-value stores
	#22	Search engines
	#38	Time Series DBMS

Website

cratedb.com

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

prometheus.io

www.tigrisdata.com

github.com/torodb/server

Technical documentation

cratedb.com/docs

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

prometheus.io/docs

www.tigrisdata.com/docs

Developer

Crate

Microsoft

Tigris Data, Inc.

8Kdata

Initial release

2013

1989

2015

2022

2016

Current release

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

commercial

restricted free version is available

Open Source

Apache 2.0

Open Source

Apache Version 2.0

Open Source

AGPL-V3

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

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Implementation language

Java

C++

Java

Server operating systems

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

Linux
Windows

Linux
macOS
Windows

All OS with a Java 7 VM

Data scheme

Flexible Schema (defined schema, partial schema, schema free)

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data only

yes

string, integer, double, boolean, date, object_id

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

Import of XML data possible

Secondary indexes

yes

SQL

Support of SQL

yes, but no triggers and constraints, and PostgreSQL compatibility

yes

APIs and other access methods

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

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

RESTful HTTP/JSON API

CLI Client
gRPC
RESTful HTTP API

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

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

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

Go
Java
JavaScript (Node.js)

Server-side scripts

Stored procedures

user defined functions (Javascript)

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Configurable replication on table/partition-level

yes, but depending on the SQL-Server Edition

yes

by Federation

yes

Source-replica replication

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

none

Immediate Consistency

Eventual Consistency
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

Durability

Support for making data persistent

yes

yes, using FoundationDB

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

Access rights for users and roles

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