DBMS > Adabas vs. Google BigQuery vs. Kinetica vs. Microsoft Azure Table Storage vs. NCache

System Properties Comparison Adabas vs. Google BigQuery vs. Kinetica vs. Microsoft Azure Table Storage vs. NCache

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

Large scale data warehouse service with append-only tables

Fully vectorized database across both GPUs and CPUs

A Wide Column Store for rapid development using massive semi-structured datasets

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

Primary database model

Secondary database models

Spatial DBMS
Time Series DBMS

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	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

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

Website

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

cloud.google.com/bigquery

www.kinetica.com

azure.microsoft.com/en-us/services/storage/tables

www.alachisoft.com/ncache

Technical documentation

cloud.google.com/bigquery/docs

docs.kinetica.com

www.alachisoft.com/resources/docs

Developer

Software AG

Google

Kinetica

Microsoft

Alachisoft

Initial release

1971

2010

2012

2005

Current release

7.1, August 2021

5.3.3, April 2024

License

Commercial or Open Source

commercial

Open Source

Enterprise Edition 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, C++

C#, .NET, .NET Core, Java

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

hosted

Linux

hosted

Linux
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

partial

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

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

with add-on product Adabas SQL Gateway

yes

SQL-like DML and DDL statements

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

APIs and other access methods

HTTP API

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

with add-on software Adabas SOA Gateway

RESTful HTTP/JSON API

JDBC
ODBC
RESTful HTTP API

RESTful HTTP API

IDistributedCache
JCache
LINQ
Proprietary native API

Supported programming languages

Natural

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C++
Java
JavaScript (Node.js)
Python

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

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

Server-side scripts

Stored procedures

in Natural

user defined functions

in JavaScript

user defined functions

support for stored procedures with SQL-Server CLR

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Notifications

Partitioning methods

Methods for storing different data on different nodes

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

none

Sharding

Implicit feature of the cloud service

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

Source-replica replication

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

yes, with selectable consistency level

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

optimistic locking

optimistic locking and pessimistic 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.

yes

GPU vRAM or System RAM

yes

User concepts

Access control

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

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Access rights for users and roles on table level

Access rights based on private key authentication or shared access signatures

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

More information provided by the system vendor

Specific characteristics

NCache has been the market leader in .NET Distributed Caching since 2005 . NCache...
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Competitive advantages

NCache is 100% .NET/ .NET Core based which fully supports ASP.NET Core Sessions ,...
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Typical application scenarios

NCache enables industries like retail, finance, banking IoT, travel, ecommerce, healthcare...
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Key customers

Bank of America, Citi, Natures Way, Charter Spectrum, Barclays, Henry Schein, GBM,...
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Market metrics

Market Leader in .NET Distributed Caching since 2005.
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Licensing and pricing models

NCache Open Source is free on an as-is basis without any support. NCache Enterprise...
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