DBMS > HyperSQL vs. Microsoft Azure AI Search vs. NSDb vs. Spark SQL vs. Transbase

System Properties Comparison HyperSQL vs. Microsoft Azure AI Search vs. NSDb vs. Spark SQL vs. Transbase

Editorial information provided by DB-Engines

Name

Description

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

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

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Spark SQL is a component on top of 'Spark Core' for structured data processing

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Secondary database models

Vector DBMS

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

Score	3.90
Rank	#85	Overall
	#46	Relational DBMS

Score	5.71
Rank	#64	Overall
	#8	Search engines

Score	0.00
Rank	#396	Overall
	#42	Time Series DBMS

Score	19.15
Rank	#33	Overall
	#20	Relational DBMS

Score	0.15
Rank	#337	Overall
	#147	Relational DBMS

Website

hsqldb.org

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

nsdb.io

spark.apache.org/sql

www.transaction.de/en/products/transbase.html

Technical documentation

hsqldb.org/web/hsqlDocsFrame.html

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

nsdb.io/Architecture

spark.apache.org/docs/latest/sql-programming-guide.html

www.transaction.de/en/products/transbase/features.html

Developer

Microsoft

Apache Software Foundation

Transaction Software GmbH

Initial release

2001

2015

2017

2014

1987

Current release

2.7.2, June 2023

3.5.0 ( 2.13), September 2023

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

based on BSD license

commercial

Open Source

Apache Version 2.0

Open Source

Apache 2.0

commercial

free development license

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

Java, Scala

Scala

C and C++

Server operating systems

All OS with a Java VM

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

hosted

Linux
macOS

Linux
OS X
Windows

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

yes

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.

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

yes

SQL-like query language

SQL-like DML and DDL statements

yes

APIs and other access methods

HTTP API

JDBC via HTTP
JDBC
ODBC

RESTful HTTP API

gRPC
HTTP REST
WebSocket

JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

All languages supporting JDBC/ODBC
Java

C#
Java
JavaScript
Python

Java
Scala

Java
Python
R
Scala

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

Java, SQL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

Sharding

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Implicit feature of the cloud service

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

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

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

HyperSQL DataBase flaw leaves library vulnerable to RCE
24 October 2022, The Daily Swig

Introduction to JDBC with HSQLDB tutorial
14 November 2022, TheServerSide.com

provided by Google News

Announcing updates to Azure AI Search to help organizations build and scale generative AI applications
4 April 2024, azure.microsoft.com

Public Preview of Azure OpenAI and AI Search in-app connectors for Logic Apps (Standard) | Azure updates
2 April 2024, azure.microsoft.com

Microsoft’s Azure AI Search updated with increased storage, vector index size
5 April 2024, InfoWorld

Microsoft Azure AI adds storage power, large RAG app support
5 April 2024, VentureBeat

Microsoft Azure AI Search just got a massive storage increase - here's what you need to know
8 April 2024, ITPro

provided by Google News

Use Amazon Athena with Spark SQL for your open-source transactional table formats | Amazon Web Services
24 January 2024, AWS Blog

What is Apache Spark? The big data platform that crushed Hadoop
3 April 2024, InfoWorld

Cracking the Apache Spark Interview: 80+ Top Questions and Answers for 2024
1 April 2024, Simplilearn

1.5 Years of Spark Knowledge in 8 Tips | by Michael Berk
23 December 2023, Towards Data Science

Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS | Amazon Web Services
18 October 2023, AWS Blog

provided by Google News

Share this page