SQLServer Flex @ STACKIT offers a managed version of SQL Server with adjustable CPU, RAM, storage amount and speed, in enterprise grade to perfectly match all application requirements. All services are 100% GDPR-compliant.

Implementation language

C++

Java

C++, JavaScript

Server operating systems

FreeBSD
Linux
macOS
Windows

hosted

Linux
Windows

All OS with a Java VM

Linux
OS X
Windows

Data scheme

Fixed schema

yes

schema-free

yes

Typing

predefined data types such as float or date

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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.

Can index from XML

yes

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

RESTful HTTP API

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

JCache
JPA
RESTful HTTP API

RESTful HTTP API

Supported programming languages

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

C#
Java
JavaScript
Python

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

.Net
C++
Java

JavaScript

Server-side scripts

Stored procedures

user defined functions

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

yes

Triggers

yes

Live Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Partitioning is done manually, search queries against distributed index is supported

Sharding

Implicit feature of the cloud service

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

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication based on Galera library

yes

Implicit feature of the cloud service

yes, but depending on the SQL-Server Edition

yes, with selectable consistency level

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

isolated transactions for atomic changes and binary logging for safe writes

ACID

configurable

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Manticore index.

yes

optionally

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

yes

using Azure authentication

fine grained access rights according to SQL-standard

authentification to access the cache via certificates or http basic authentication

yes

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