DBMS > 4D vs. Adabas vs. Lovefield vs. Microsoft Azure Data Explorer vs. Transwarp Hippo

System Properties Comparison 4D vs. Adabas vs. Lovefield vs. Microsoft Azure Data Explorer vs. Transwarp Hippo

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

OLTP - DBMS for mainframes and Linux/Unix/Windows environments

used typically together with the Natural programming platform

Embeddable relational database for web apps written in pure JavaScript

Fully managed big data interactive analytics platform

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

Primary database model

column oriented

Secondary database models

Document store

If a column is of type dynamic docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types/dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store

this is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine

support for complex search expressions docs.microsoft.com/en-us/azure/kusto/query/parseoperator FTS, Geospatial docs.microsoft.com/en-us/azure/kusto/query/geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS

see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis

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

Score	2.47
Rank	#110	Overall
	#54	Relational DBMS

Score	2.79
Rank	#102	Overall
	#2	Multivalue DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	3.80
Rank	#81	Overall
	#43	Relational DBMS

Score	0.05
Rank	#386	Overall
	#14	Vector DBMS

Website

www.4d.com

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

google.github.io/lovefield

azure.microsoft.com/services/data-explorer

www.transwarp.cn/en/subproduct/hippo

Technical documentation

developer.4d.com

github.com/google/lovefield/blob/master/docs/spec_index.md

docs.microsoft.com/en-us/azure/data-explorer

Developer

4D, Inc

Software AG

Google

Microsoft

Initial release

1984

1971

2014

2019

2023

Current release

v20, April 2023

2.1.12, February 2017

cloud service with continuous releases

1.0, May 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

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

JavaScript

C++

Server operating systems

OS X
Windows

BS2000
Linux
Unix
Windows
z/OS
z/VSE

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

tested with Chrome, Firefox, IE, Safari

hosted

Linux
macOS

Data scheme

yes

Fixed schema with schema-less datatypes (dynamic)

Typing

predefined data types such as float or date

yes

bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types

Vector, Numeric and String

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

all fields are automatically indexed

SQL

Support of SQL

yes

close to SQL 92

yes

with add-on product Adabas SQL Gateway

SQL-like query language

via JavaScript builder pattern

Kusto Query Language (KQL), SQL subset

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

HTTP API

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

with add-on software Adabas SOA Gateway

Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API

RESTful HTTP API

Supported programming languages

4D proprietary IDE
PHP

Natural

JavaScript

.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R

C++
Java
Python

Server-side scripts

Stored procedures

yes

in Natural

Yes, possible languages: KQL, Python, R

Triggers

yes

Using read-only observers

yes

see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy

Partitioning methods

Methods for storing different data on different nodes

none

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

none

Sharding

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes, with add-on product Event Replicator

none

yes

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

MapReduce

Offers an API for user-defined Map/Reduce methods

Spark connector (open source): github.com/Azure/azure-kusto-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

using MemoryDB

yes

User concepts

Access control

Users and groups

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

Azure Active Directory Authentication

Role based access control and fine grained access rights

More information provided by the system vendor

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More resources

DB-Engines blog posts

MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

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