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++

Prolog, Rust

Java

Server operating systems

FreeBSD
Linux
macOS
Windows

Linux
Windows

Linux

Linux
macOS

for devlopment

Data scheme

Fixed schema

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

depending on connected data-source

SQL

Support of SQL

SQL-like query language

yes

SQL-like query language (WOQL)

yes

APIs and other access methods

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

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

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

JDBC
RESTful HTTP API
Trino CLI

Supported programming languages

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

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

JavaScript
Python

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

user defined functions

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

yes

yes, depending on connected data-source

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

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

Graph Partitioning

depending on connected data-source

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication based on Galera library

yes, but depending on the SQL-Server Edition

Journaling Streams

depending on connected data-source

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

depending on connected data-source

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

depending on connected data-source

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

in-memory journaling

depending on connected data-source

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Role-based access control

SQL standard access control

More information provided by the system vendor

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