DBMS > Apache Impala vs. BaseX vs. HyperSQL vs. Teradata

System Properties Comparison Apache Impala vs. BaseX vs. HyperSQL vs. Teradata

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Light-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Relational DBMS

Native XML DBMS

Relational DBMS

Secondary database models

Document store

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	1.84
Rank	#135	Overall
	#4	Native XML DBMS

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

Score	44.87
Rank	#22	Overall
	#15	Relational DBMS

Website

Technical documentation

impala.apache.org/impala-docs.html

docs.basex.org

hsqldb.org/web/hsqlDocsFrame.html

docs.teradata.com

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

BaseX GmbH

Teradata

Initial release

2013

2007

2001

1984

Current release

4.1.0, June 2022

10.7, August 2023

2.7.2, June 2023

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

BSD license

Open Source

based on BSD license

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

C++

Java

Server operating systems

Linux

Linux
OS X
Windows

All OS with a Java VM

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

hosted
Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

XQuery supports types

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.

yes

Secondary indexes

yes

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

SQL-like DML and DDL statements

yes

SQL 2016 + extensions

APIs and other access methods

JDBC
ODBC

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

HTTP API

JDBC via HTTP
JDBC
ODBC

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

Supported programming languages

All languages supporting JDBC/ODBC

Actionscript
C
C#
Haskell
Java
JavaScript

Node.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic

All languages supporting JDBC/ODBC
Java

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Java, SQL

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

via events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

Multi-source replication
Source-replica 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

Foreign keys

Referential integrity

yes

Transaction concepts

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

multiple readers, single writer

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Users with fine-grained authorization concept on 4 levels

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

Teradata is the most popular data warehouse DBMS
2 April 2013, Paul Andlinger

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Recent citations in the news

Apache Impala 4 Supports Operator Multi-Threading
29 July 2021, iProgrammer

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

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XML Injection Attacks: What to Know About XPath, XQuery, XXE & More
18 May 2022, Hashed Out by The SSL Store™

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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

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Teradata Fails to Block Software Broker From Selling Its Products
3 June 2024, Bloomberg Law

Teradata Buys Data Archiving Firm RainStor
31 May 2024, Data Center Knowledge

Lakehouse dam breaks after departure of long-time Teradata CTO
1 May 2024, The Register

Is There Now An Opportunity In Teradata Corporation (NYSE:TDC)?
28 May 2024, Yahoo Finance

Chief Customer Officer Of Teradata Sold 25% Of Their Shares
12 May 2024, Simply Wall St

provided by Google News

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