DBMS > Apache Impala vs. Apache Jena - TDB vs. HEAVY.AI vs. NSDb

System Properties Comparison Apache Impala vs. Apache Jena - TDB vs. HEAVY.AI vs. NSDb

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

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

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

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

Primary database model

Secondary database models

Document store

Spatial DBMS

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	3.75
Rank	#84	Overall
	#3	RDF stores

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

impala.apache.org

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

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

nsdb.io

Technical documentation

impala.apache.org/impala-docs.html

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

docs.heavy.ai

nsdb.io/Architecture

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Apache Software Foundation

originally developed by HP Labs

HEAVY.AI, Inc.

Initial release

2013

2000

2016

2017

Current release

4.1.0, June 2022

4.9.0, July 2023

5.10, January 2022

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache License, Version 2.0

Open Source

Apache Version 2; enterprise edition available

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

C++ and CUDA

Java, Scala

Server operating systems

Linux

All OS with a Java VM

Linux

Linux
macOS

Data scheme

yes

RDF Schemas

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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

SQL

Support of SQL

SQL-like DML and DDL statements

yes

SQL-like query language

APIs and other access methods

JDBC
ODBC

Fuseki

REST-style SPARQL HTTP Interface
Jena RDF API
RIO

RDF Input/Output

JDBC
ODBC
Thrift
Vega

gRPC
HTTP REST
WebSocket

Supported programming languages

All languages supporting JDBC/ODBC

Java

All languages supporting JDBC/ODBC/Thrift
Python

Java
Scala

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Triggers

yes

via event handler

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Round robin

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

TDB Transactions

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

In-memory capabilities

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

yes

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Access control via Jena Security

fine grained access rights according to SQL-standard

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