DBMS > Microsoft Azure Synapse Analytics vs. SAP Advantage Database Server vs. Spark SQL vs. YottaDB

System Properties Comparison Microsoft Azure Synapse Analytics vs. SAP Advantage Database Server vs. Spark SQL vs. YottaDB

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Editorial information provided by DB-Engines

Name

SAP Advantage Database Server seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Low-cost RDBMS with access to ISAM and FoxPro data structures

Spark SQL is a component on top of 'Spark Core' for structured data processing

A fast and solid embedded Key-value store

Primary database model

Relational DBMS

Key-value store

Secondary database models

Relational DBMS

using the Octo plugin

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

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	0.28
Rank	#306	Overall
	#44	Key-value stores

Website

azure.microsoft.com/services/synapse-analytics

www.sap.com/products/advantage-database-server.html

spark.apache.org/sql

yottadb.com

Technical documentation

docs.microsoft.com/azure/synapse-analytics

spark.apache.org/docs/latest/sql-programming-guide.html

yottadb.com/resources/documentation

Developer

Microsoft

Sybase, SAP

Apache Software Foundation

YottaDB, LLC

Initial release

2016

1993

2014

2001

Current release

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

AGPL 3.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Scala

Server operating systems

hosted

Linux
Windows

Linux
OS X
Windows

Docker
Linux

Data scheme

yes

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

by using the Octo plugin

APIs and other access methods

ADO.NET
JDBC
ODBC

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

JDBC
ODBC

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

C#
Java
PHP

Delphi
Perl
PHP

Java
Python
R
Scala

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

Transact SQL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

none

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

yes

Transaction concepts

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

ACID

optimistic locking

Concurrency

Support for concurrent manipulation of data

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.

caching of (temporary) tables can be configured

yes

User concepts

Access control

yes

fine grained access rights according to SQL-standard

Users and groups based on OS-security mechanisms

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