DBMS > Apache Impala vs. Heroic vs. Kinetica vs. OpenQM vs. searchxml

System Properties Comparison Apache Impala vs. Heroic vs. Kinetica vs. OpenQM vs. searchxml

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Fully vectorized database across both GPUs and CPUs

QpenQM is a high-performance, self-tuning, multi-value DBMS

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Native XML DBMS
Search engine

Secondary database models

Document store

Spatial DBMS
Time Series DBMS

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Score	0.00
Rank	#383	Overall
	#7	Native XML DBMS
	#25	Search engines

Website

impala.apache.org

github.com/spotify/heroic

www.kinetica.com

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

www.searchxml.net/category/products

Technical documentation

impala.apache.org/impala-docs.html

spotify.github.io/heroic

docs.kinetica.com

www.searchxml.net/support/handouts

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Spotify

Kinetica

Rocket Software, originally Martin Phillips

informationpartners gmbh

Initial release

2013

2014

2012

1993

2015

Current release

4.1.0, June 2022

7.1, August 2021

3.4-12

1.0

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache 2.0

commercial

Open Source

GPLv2, extended commercial license 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

C++

Java

C, C++

C++

Server operating systems

Linux

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Windows

Data scheme

yes

schema-free

yes

with some exceptions

schema-free

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.

yes

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC

HQL (Heroic Query Language, a JSON-based language)
HTTP API

JDBC
ODBC
RESTful HTTP API

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

All languages supporting JDBC/ODBC

C++
Java
JavaScript (Node.js)
Python

.Net
Basic
C
Java
Objective C
PHP
Python

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

user defined functions

yes

on the application server

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

Source-replica replication

yes

sychronisation to multiple collections

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

Eventual Consistency
Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

multiple readers, single writer

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

GPU vRAM or System RAM

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Access rights for users and roles on table level

Access rights can be defined down to the item level

Domain, group and role-based access control at the document level and for application services

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More resources

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

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14 July 2022, Datanami

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

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

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26 March 2024, Datanami

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18 March 2024, SiliconANGLE News

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18 March 2024, GlobeNewswire

Kinetica Delivers Real-Time Vector Similarity Search
20 March 2024, Datanami

Kinetica Delivers Real-Time Vector Similarity Search
22 March 2024, Geospatial World

provided by Google News

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