DBMS > 4D vs. EJDB vs. IBM Cloudant vs. LevelDB vs. Microsoft Azure Data Explorer

System Properties Comparison 4D vs. EJDB vs. IBM Cloudant vs. LevelDB vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

Database as a Service offering based on Apache CouchDB

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Fully managed big data interactive analytics platform

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	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	2.68
Rank	#106	Overall
	#20	Document stores

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	4.38
Rank	#77	Overall
	#41	Relational DBMS

Website

www.4d.com

github.com/Softmotions/ejdb

www.ibm.com/products/cloudant

github.com/google/leveldb

azure.microsoft.com/services/data-explorer

Technical documentation

developer.4d.com

github.com/Softmotions/ejdb/blob/master/README.md

cloud.ibm.com/docs/Cloudant

github.com/google/leveldb/blob/main/doc/index.md

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

Developer

4D, Inc

Softmotions

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Google

Microsoft

Initial release

1984

2012

2010

2011

2019

Current release

v20, April 2023

1.23, February 2021

cloud service with continuous releases

License

Commercial or Open Source

commercial

Open Source

GPLv2

commercial

Open Source

BSD

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

Erlang

C++

Server operating systems

OS X
Windows

server-less

hosted

Illumos
Linux
OS X
Windows

hosted

Data scheme

yes

schema-free

Fixed schema with schema-less datatypes (dynamic)

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

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

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

Kusto Query Language (KQL), SQL subset

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

in-process shared library

RESTful HTTP/JSON API

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

Supported programming languages

4D proprietary IDE
PHP

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

C#
Java
JavaScript
Objective-C
PHP
Ruby

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

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

Server-side scripts

Stored procedures

yes

View functions (Map-Reduce) in JavaScript

Yes, possible languages: KQL, Python, R

Triggers

yes

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

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

Multi-source replication
Source-replica replication

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

yes

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

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

typically not needed, however similar functionality with collection joins possible

Transaction concepts

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

ACID

atomic operations within a document possible

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Optimistic locking

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

yes

In-memory capabilities

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

User concepts

Access control

Users and groups

Access rights for users can be defined per database

Azure Active Directory Authentication

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