DBMS > Adabas vs. Cloudflare Workers KV vs. EsgynDB vs. Google BigQuery vs. LokiJS

System Properties Comparison Adabas vs. Cloudflare Workers KV vs. EsgynDB vs. Google BigQuery vs. LokiJS

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 global, low-latency, key-value store for applications on Cloudflare with exceptionally high read volumes and low-latency.

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Large scale data warehouse service with append-only tables

In-memory JavaScript DBMS

Primary database model

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

Score	2.79
Rank	#102	Overall
	#2	Multivalue DBMS

Score	0.39
Rank	#274	Overall
	#39	Key-value stores

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	0.49
Rank	#260	Overall
	#42	Document stores

Website

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

www.cloudflare.com/developer-platform/workers-kv

www.esgyn.cn

cloud.google.com/bigquery

github.com/techfort/LokiJS

Technical documentation

developers.cloudflare.com/kv/api

cloud.google.com/bigquery/docs

techfort.github.io/LokiJS

Developer

Software AG

Cloudflare

Esgyn

Google

Initial release

1971

2018

2015

2010

2014

License

Commercial or Open Source

commercial

Open Source

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++, Java

JavaScript

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

hosted

Linux

hosted

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

Data scheme

yes

schema-free

yes

schema-free

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.

Secondary indexes

yes

via views

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

yes

APIs and other access methods

HTTP API

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

with add-on software Adabas SOA Gateway

HTTP REST
Proprietary protocol

ADO.NET
JDBC
ODBC

RESTful HTTP/JSON API

JavaScript API

Supported programming languages

Natural

C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala

All languages supporting JDBC/ODBC/ADO.Net

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

JavaScript

Server-side scripts

Stored procedures

in Natural

Java Stored Procedures

user defined functions

in JavaScript

View functions in JavaScript

Triggers

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

yes

Multi-source replication between multi datacenters

none

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

none

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

atomic operations within a single collection possible

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.

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)

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