DBMS > Apache IoTDB vs. Apache Jena - TDB vs. HarperDB vs. HEAVY.AI vs. jBASE

System Properties Comparison Apache IoTDB vs. Apache Jena - TDB vs. HarperDB vs. HEAVY.AI vs. jBASE

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

A RDF storage and query DBMS, shipped as an optional-use component of the Apache Jena framework

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.

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

A robust multi-value DBMS comprising development tools and middleware

Primary database model

Secondary database models

Spatial DBMS

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

Score	1.31
Rank	#164	Overall
	#14	Time Series DBMS

Score	3.62
Rank	#83	Overall
	#3	RDF stores

Score	0.60
Rank	#244	Overall
	#38	Document stores

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	1.49
Rank	#156	Overall
	#3	Multivalue DBMS

Website

iotdb.apache.org

jena.apache.org/documentation/tdb/index.html

www.harperdb.io

github.com/heavyai/heavydb
www.heavy.ai

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

Technical documentation

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

jena.apache.org/documentation/tdb/index.html

docs.harperdb.io/docs

docs.heavy.ai

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

Developer

Apache Software Foundation

originally developed by HP Labs

HarperDB

HEAVY.AI, Inc.

Rocket Software (formerly Zumasys)

Initial release

2018

2000

2017

2016

1991

Current release

1.1.0, April 2023

4.9.0, July 2023

3.1, August 2021

5.10, January 2022

5.7

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache License, Version 2.0

commercial

free community edition available

Open Source

Apache Version 2; enterprise edition available

commercial

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

Node.js

C++ and CUDA

Server operating systems

All OS with a Java VM (>= 1.8)

All OS with a Java VM

Linux
OS X

Linux

AIX
Linux
Windows

Data scheme

yes

RDF Schemas

dynamic schema

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON data types

yes

optional

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

SQL-like query language

SQL-like data manipulation statements

yes

Embedded SQL for jBASE in BASIC

APIs and other access methods

JDBC
Native API

Fuseki

REST-style SPARQL HTTP Interface
Jena RDF API
RIO

RDF Input/Output

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

JDBC
ODBC
Thrift
Vega

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

Java

.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

All languages supporting JDBC/ODBC/Thrift
Python

.Net
Basic
Jabbascript
Java

Server-side scripts

Stored procedures

yes

Custom Functions

since release 3.1

yes

Triggers

yes

via event handler

yes

Partitioning methods

Methods for storing different data on different nodes

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

none

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

Sharding

Round robin

Sharding

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

yes

the nodes on which a table resides can be defined

Multi-source replication

yes

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

Foreign keys

Referential integrity

Transaction concepts

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

ACID

TDB Transactions

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

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

Access control via Jena Security

Access rights for users and roles

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

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