DBMS > Adabas vs. Google Cloud Firestore vs. HugeGraph vs. NCache vs. SQLite

System Properties Comparison Adabas vs. Google Cloud Firestore vs. HugeGraph vs. NCache vs. SQLite

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

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.

A fast-speed and highly-scalable Graph DBMS

Open-Source and Enterprise in-memory Key-Value Store

Widely used embeddable, in-process RDBMS

Primary database model

Secondary database models

Document store
Search engine

Using distributed Lucene

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

Score	2.79
Rank	#102	Overall
	#2	Multivalue DBMS

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	0.96
Rank	#195	Overall
	#29	Key-value stores

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

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

firebase.google.com/products/firestore

github.com/hugegraph
hugegraph.apache.org

www.alachisoft.com/ncache

www.sqlite.org

Technical documentation

firebase.google.com/docs/firestore

hugegraph.apache.org/docs

www.alachisoft.com/resources/docs

www.sqlite.org/docs.html

Developer

Software AG

Google

Baidu

Alachisoft

Dwayne Richard Hipp

Initial release

1971

2017

2018

2005

2000

Current release

0.9

5.3.3, April 2024

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Enterprise Edition available

Open Source

Public Domain

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

Java

C#, .NET, .NET Core, Java

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

hosted

Linux
macOS
Unix

Linux
Windows

server-less

Data scheme

yes

schema-free

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

partial

Supported data types are Lists, Queues, Hashsets, Dictionary and Counter

yes

not rigid because of 'dynamic typing' concept.

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

also supports composite index and range index

yes

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

SQL-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.

yes

SQL-92 is not fully supported

APIs and other access methods

HTTP API

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

with add-on software Adabas SOA Gateway

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

Java API
RESTful HTTP API
TinkerPop Gremlin

IDistributedCache
JCache
LINQ
Proprietary native API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

Natural

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

Groovy
Java
Python

.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

in Natural

yes, Firebase Rules & Cloud Functions

asynchronous Gremlin script jobs

support for stored procedures with SQL-Server CLR

Triggers

yes, with Cloud Functions

yes

Notifications

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

yes

depending on used storage backend, e.g. Cassandra and HBase

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

Multi-source replication

yes

depending on used storage backend, e.g. Cassandra and HBase

yes, with selectable consistency level

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

via hugegraph-spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Eventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology

Foreign keys

Referential integrity

yes

edges in graph

yes

Transaction concepts

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

ACID

yes

ACID

optimistic locking and pessimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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.

Users, roles and permissions

Authentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)

More information provided by the system vendor

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