DBMS > HugeGraph vs. Microsoft Azure Data Explorer vs. Sadas Engine vs. SiriDB vs. SQLite

System Properties Comparison HugeGraph vs. Microsoft Azure Data Explorer vs. Sadas Engine vs. SiriDB vs. SQLite

Editorial information provided by DB-Engines

Name

Description

A fast-speed and highly-scalable Graph DBMS

Fully managed big data interactive analytics platform

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Open Source Time Series DBMS

Widely used embeddable, in-process RDBMS

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	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	3.80
Rank	#81	Overall
	#43	Relational DBMS

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Score	0.07
Rank	#378	Overall
	#42	Time Series DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

github.com/hugegraph
hugegraph.apache.org

azure.microsoft.com/services/data-explorer

www.sadasengine.com

siridb.com

www.sqlite.org

Technical documentation

hugegraph.apache.org/docs

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

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

docs.siridb.com

www.sqlite.org/docs.html

Developer

Baidu

Microsoft

SADAS s.r.l.

Cesbit

Dwayne Richard Hipp

Initial release

2018

2019

2006

2017

2000

Current release

0.9

cloud service with continuous releases

8.0

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free trial version available

Open Source

MIT License

Open Source

Public Domain

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

Java

C++

Server operating systems

Linux
macOS
Unix

hosted

AIX
Linux
Windows

Linux

server-less

Data scheme

yes

Fixed schema with schema-less datatypes (dynamic)

yes

dynamic column types

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

yes

Numeric data

yes

not rigid because of 'dynamic typing' concept.

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

also supports composite index and range index

all fields are automatically indexed

yes

SQL

Support of SQL

Kusto Query Language (KQL), SQL subset

yes

SQL-92 is not fully supported

APIs and other access methods

Java API
RESTful HTTP API
TinkerPop Gremlin

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

JDBC
ODBC
Proprietary protocol

HTTP API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

Groovy
Java
Python

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

.Net
C
C#
C++
Groovy
Java
PHP
Python

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

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

Yes, possible languages: KQL, Python, R

Triggers

yes

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

yes

Partitioning methods

Methods for storing different data on different nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

Sharding

Implicit feature of the cloud service

horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

yes

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

none

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

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

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

managed by 'Learn by Usage'

yes

User concepts

Access control

Users, roles and permissions

Azure Active Directory Authentication

Access rights for users, groups and roles according to SQL-standard

simple rights management via user accounts

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