DBMS > Adabas vs. Apache Impala vs. Google Cloud Firestore vs. LokiJS vs. Oracle

System Properties Comparison Adabas vs. Apache Impala vs. Google Cloud Firestore vs. LokiJS vs. Oracle

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

Analytic DBMS for Hadoop

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.

In-memory JavaScript DBMS

Widely used RDBMS

Primary database model

Secondary database models

Document store

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	2.79
Rank	#102	Overall
	#2	Multivalue DBMS

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	0.49
Rank	#260	Overall
	#42	Document stores

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Website

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

impala.apache.org

firebase.google.com/products/firestore

github.com/techfort/LokiJS

www.oracle.com/database

Technical documentation

impala.apache.org/impala-docs.html

firebase.google.com/docs/firestore

techfort.github.io/LokiJS

docs.oracle.com/en/database

Developer

Software AG

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Google

Oracle

Initial release

1971

2013

2017

2014

1980

Current release

4.1.0, June 2022

23c, September 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

commercial

Open Source

commercial

restricted free version is available

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++

JavaScript

C and C++

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux

hosted

server-less, requires a JavaScript environment (browser, Node.js)

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Data scheme

yes

schema-free

yes

Schemaless in JSON and XML columns

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

via views

yes

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

SQL-like DML and DDL statements

yes

with proprietary extensions

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

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

JavaScript API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

Natural

All languages supporting JDBC/ODBC

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

JavaScript

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

Server-side scripts

Stored procedures

in Natural

yes

user defined functions and integration of map-reduce

yes, Firebase Rules & Cloud Functions

View functions in JavaScript

PL/SQL

also stored procedures in Java possible

Triggers

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

none

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

selectable replication factor

Multi-source replication

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Using Cloud Dataflow

yes

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

atomic operations within a single collection possible

ACID

isolation level can be parameterized

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

yes

In-memory capabilities

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

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

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 Apache Sentry and Kerberos

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

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