DBMS > Adabas vs. AgensGraph vs. Google BigQuery vs. NCache vs. Rockset

System Properties Comparison Adabas vs. AgensGraph vs. Google BigQuery vs. NCache vs. Rockset

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

Multi-model database supporting relational and graph data models and built upon PostgreSQL

Large scale data warehouse service with append-only tables

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

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Primary database model

Multivalue DBMS

Graph DBMS
Relational DBMS

Relational DBMS

Key-value store

Document store

Secondary database models

Document store
Search engine

Using distributed Lucene

Relational DBMS
Search engine

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

Score	3.58
Rank	#91	Overall
	#1	Multivalue DBMS

Score	0.16
Rank	#333	Overall
	#30	Graph DBMS
	#146	Relational DBMS

Score	61.90
Rank	#19	Overall
	#13	Relational DBMS

Score	0.98
Rank	#196	Overall
	#29	Key-value stores

Score	0.84
Rank	#209	Overall
	#35	Document stores

Website

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

bitnine.net/agensgraph

cloud.google.com/bigquery

www.alachisoft.com/ncache

rockset.com

Technical documentation

bitnine.net/documentation

cloud.google.com/bigquery/docs

www.alachisoft.com/resources/docs

docs.rockset.com

Developer

Software AG

Bitnine Global Inc.

Google

Alachisoft

Rockset

Initial release

1971

2016

2010

2005

2019

Current release

2.1, December 2018

5.3.3, April 2024

License

Commercial or Open Source

commercial

Open Source

Apache License 2.0

commercial

Open Source

Enterprise Edition available

commercial

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#, .NET, .NET Core, Java

C++

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux
OS X
Windows

hosted

Linux
Windows

hosted

Data scheme

yes

depending on used data model

yes

schema-free

Typing

predefined data types such as float or date

yes

partial

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

dynamic typing

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.

ingestion from XML files supported

Secondary indexes

yes

all fields are automatically indexed

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

yes

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

Read-only SQL queries, including 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

Cypher Query Language
JDBC

RESTful HTTP/JSON API

IDistributedCache
JCache
LINQ
Proprietary native API

HTTP REST

Supported programming languages

Natural

C
Java
JavaScript
Python

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

in Natural

yes

user defined functions

in JavaScript

support for stored procedures with SQL-Server CLR

Triggers

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

no, but can be realized using table inheritance

none

yes

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

Source-replica replication

yes, with selectable consistency level

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

Eventual Consistency

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 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

User concepts

Access control

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

fine grained access rights according to SQL-standard

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

Google Cloud Identity & Access Management (IAM)

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

Access rights for users and organizations can be defined via Rockset console

More information provided by the system vendor

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