DBMS > Graph Engine vs. HyperSQL vs. Microsoft Azure AI Search vs. SQLite vs. TimescaleDB

System Properties Comparison Graph Engine vs. HyperSQL vs. Microsoft Azure AI Search vs. SQLite vs. TimescaleDB

Editorial information provided by DB-Engines

Name

Description

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Search-as-a-service for web and mobile app development

Widely used embeddable, in-process RDBMS

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Graph DBMS
Key-value store

Secondary database models

Vector DBMS

Relational DBMS

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

Score	0.62
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	3.90
Rank	#85	Overall
	#46	Relational DBMS

Score	5.71
Rank	#64	Overall
	#8	Search engines

Score	116.01
Rank	#10	Overall
	#7	Relational DBMS

Score	4.87
Rank	#74	Overall
	#4	Time Series DBMS

Website

www.graphengine.io

hsqldb.org

azure.microsoft.com/en-us/services/search

www.sqlite.org

www.timescale.com

Technical documentation

www.graphengine.io/docs/manual

hsqldb.org/web/hsqlDocsFrame.html

learn.microsoft.com/en-us/azure/search

www.sqlite.org/docs.html

docs.timescale.com

Developer

Microsoft

Dwayne Richard Hipp

Timescale

Initial release

2010

2001

2015

2000

2017

Current release

2.7.2, June 2023

3.45.3 (15 April 2024), April 2024

2.13.0, November 2023

License

Commercial or Open Source

Open Source

MIT License

Open Source

based on BSD license

commercial

Open Source

Public Domain

Open Source

Apache 2.0

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

.NET and C

Java

Server operating systems

.NET

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

hosted

server-less

Linux
OS X
Windows

Data scheme

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex 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

SQL

Support of SQL

yes

SQL-92 is not fully supported

yes

full PostgreSQL SQL syntax

APIs and other access methods

RESTful HTTP API

HTTP API

JDBC via HTTP
JDBC
ODBC

RESTful HTTP API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

C#
C++
F#
Visual Basic

All languages supporting JDBC/ODBC
Java

C#
Java
JavaScript
Python

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

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

Java, SQL

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Sharding

Implicit feature of the cloud service

none

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Implicit feature of the cloud service

none

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

via file-system locks

yes

Durability

Support for making data persistent

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes

using Azure authentication

fine grained access rights according to SQL-standard

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