DBMS > Adabas vs. Apache Kylin vs. Google Cloud Firestore vs. Microsoft SQL Server vs. OrientDB

System Properties Comparison Adabas vs. Apache Kylin vs. Google Cloud Firestore vs. Microsoft SQL Server vs. OrientDB

Editorial information provided by DB-Engines

Name

Description

OLTP - DBMS for mainframes and Linux/Unix/Windows environments

used typically together with the Natural programming platform

A distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stack

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

Microsofts flagship relational DBMS

Multi-model DBMS (Document, Graph, Key/Value)

Primary database model

Document store
Graph DBMS
Key-value store

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	3.17
Rank	#94	Overall
	#1	Multivalue DBMS

Score	1.18
Rank	#172	Overall
	#79	Relational DBMS

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	3.19
Rank	#93	Overall
	#16	Document stores
	#7	Graph DBMS
	#14	Key-value stores

Website

www.softwareag.com/en_corporate/platform/adabas-natural.html

kylin.apache.org

firebase.google.com/products/firestore

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

orientdb.org

Technical documentation

kylin.apache.org/docs

firebase.google.com/docs/firestore

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

www.orientdb.com/docs/last/index.html

Developer

Software AG

Apache Software Foundation, originally contributed from eBay Inc

Google

Microsoft

OrientDB LTD; CallidusCloud; SAP

Initial release

1971

2015

2017

1989

2010

Current release

3.1.0, July 2020

SQL Server 2022, November 2022

3.2.29, March 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

restricted free version is available

Open Source

Apache version 2

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

C++

Java

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux

hosted

Linux
Windows

All OS with a Java JDK (>= JDK 6)

Data scheme

yes

schema-free

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

ANSI SQL for queries (using Apache Calcite)

yes

SQL-like query language, no joins

APIs and other access methods

HTTP API

with add-on software Adabas SOA Gateway
SOAP-based API

with add-on software Adabas SOA Gateway

JDBC
ODBC
RESTful HTTP API

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

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

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

Supported programming languages

Natural

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

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

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

Server-side scripts

Stored procedures

in Natural

yes, Firebase Rules & Cloud Functions

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

Java, Javascript

Triggers

yes, with Cloud Functions

yes

Hooks

Partitioning methods

Methods for storing different data on different nodes

yes, with additonal products like Adabas Cluster Services, Adabas Parallel Services, Adabas Vista

Sharding

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

Multi-source replication

yes, but depending on the SQL-Server Edition

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Using Cloud Dataflow

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

Transaction concepts

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

ACID

yes

ACID

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.

yes

User concepts

Access control

only with OS-specific tools (e.g. IBM RACF, CA Top Secret)

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

fine grained access rights according to SQL-standard

Access rights for users and roles; record level security configurable

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