DBMS > 4D vs. HarperDB vs. Microsoft Azure Data Explorer vs. Quasardb

System Properties Comparison 4D vs. HarperDB vs. Microsoft Azure Data Explorer vs. Quasardb

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Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

Fully managed big data interactive analytics platform

Distributed, high-performance timeseries database

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	0.55
Rank	#248	Overall
	#38	Document stores

Score	4.38
Rank	#77	Overall
	#41	Relational DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Website

www.4d.com

www.harperdb.io

azure.microsoft.com/services/data-explorer

quasar.ai

Technical documentation

developer.4d.com

docs.harperdb.io/docs

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

doc.quasar.ai/master

Developer

4D, Inc

HarperDB

Microsoft

quasardb

Initial release

1984

2017

2019

2009

Current release

v20, April 2023

3.1, August 2021

cloud service with continuous releases

3.14.1, January 2024

License

Commercial or Open Source

commercial

free community edition available

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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

Node.js

C++

Server operating systems

OS X
Windows

Linux
OS X

hosted

BSD
Linux
OS X
Windows

Data scheme

yes

dynamic schema

Fixed schema with schema-less datatypes (dynamic)

schema-free

Typing

predefined data types such as float or date

yes

JSON data types

yes

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

yes

integer and binary

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

yes

with tags

SQL

Support of SQL

yes

close to SQL 92

SQL-like data manipulation statements

Kusto Query Language (KQL), SQL subset

SQL-like query language

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

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

HTTP API

Supported programming languages

4D proprietary IDE
PHP

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

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

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

Server-side scripts

Stored procedures

yes

Custom Functions

since release 3.1

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

A table resides as a whole on one (or more) nodes in a cluster

Sharding

Implicit feature of the cloud service

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

the nodes on which a table resides can be defined

yes

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

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

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

with Hadoop integration

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

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using LMDB

yes

by using LevelDB

In-memory capabilities

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

yes

Transient mode

User concepts

Access control

Users and groups

Access rights for users and roles

Azure Active Directory Authentication

Cryptographically strong user authentication and audit trail

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More resources

DB-Engines blog posts

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