DBMS > Apache IoTDB vs. HyperSQL vs. YugabyteDB

System Properties Comparison Apache IoTDB vs. HyperSQL vs. YugabyteDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

High-performance distributed SQL database for global, internet-scale applications. Wire and feature compatible with PostgreSQL.

Primary database model

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Wide column store

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

Score	1.40
Rank	#148	Overall
	#14	Time Series DBMS

Score	2.70
Rank	#92	Overall
	#49	Relational DBMS

Score	2.23
Rank	#107	Overall
	#53	Relational DBMS

Website

iotdb.apache.org

hsqldb.org

www.yugabyte.com

Technical documentation

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

hsqldb.org/web/hsqlDocsFrame.html

docs.yugabyte.com
github.com/yugabyte/yugabyte-db

Developer

Apache Software Foundation

Yugabyte Inc.

Initial release

2018

2001

2017

Current release

1.1.0, April 2023

2.7.2, June 2023

2024.2, December 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

based on BSD license

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C and C++

Server operating systems

All OS with a Java VM (>= 1.8)

All OS with a Java VM

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

Linux
OS X

Data scheme

yes

depending on used data model

Typing

predefined data types such as float or date

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

SQL

Support of SQL

SQL-like query language

yes

yes, PostgreSQL compatible

APIs and other access methods

JDBC
Native API

HTTP API

JDBC via HTTP
JDBC
ODBC

JDBC
YCQL, an SQL-based flexible-schema API with its roots in Cassandra Query Language
YSQL - a fully relational SQL API that is wire compatible with the SQL language in PostgreSQL

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

All languages supporting JDBC/ODBC
Java

C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
Scala

Server-side scripts

Stored procedures

yes

Java, SQL

yes

sql, plpgsql, C

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

none

Hash and Range Sharding, row-level geo-partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

none

Based on Raft distributed consensus protocol, minimum 3 replicas for continuous availability

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency

Strong consistency on writes and tunable consistency on reads

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Distributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture.

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

based on RocksDB

In-memory capabilities

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

yes

User concepts

Access control

yes

fine grained access rights according to SQL-standard

yes

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

New AMD ERAPS Feature Yields Additional Performance Gains On Zen 5
18 November 2024, Phoronix

China's database software ranks first on international authoritative list
1 September 2024, bastillepost.com

AMD EPYC 4364P & 4564P @ DDR5-4800 / DDR5-5200 vs. Intel Xeon E-2488 Review
6 June 2024, Phoronix

TsFile: A Standard Format for IoT Time Series Data
27 February 2024, The New Stack

IoTDB Provides Data Management for Industrial Edge IT
15 October 2020, The New Stack

provided by Google News

Java, JDBC and the HSQLDB database tutorial
14 November 2022, theserverside.com

HyperSQL DataBase flaw leaves library vulnerable to RCE
24 October 2022, PortSwigger

provided by Google News

Yugabyte Announces Sixth Annual Distributed SQL Summit, Unveils Keynote and Lineup of Speakers for November Hybrid Event
3 October 2024, Business Wire

Every Microsecond Counts: YugabyteDB Boosts Performance with Amazon Time Sync | Amazon Web Services
17 February 2025, Amazon Web Services

Karthik Ranganathan, Co-Founder and Co-CEO of Yugabyte – Interview Series
7 January 2025, Unite.AI

YugabyteDB evolves into a distributed PostgreSQL database for apps that need resilience and scale
19 September 2024, SiliconANGLE

YugabyteDB Unveils First Agentic AI Application and Extensible Vector Search For Deploying AI at Scale
8 April 2025, Yahoo Finance

provided by Google News

Share this page