DBMS > Apache Impala vs. GeoSpock vs. OpenQM vs. Snowflake vs. Valentina Server

System Properties Comparison Apache Impala vs. GeoSpock vs. OpenQM vs. Snowflake vs. Valentina Server

Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

Analytic DBMS for Hadoop

Spatial and temporal data processing engine for extreme data scale

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

Cloud-based data warehousing service for structured and semi-structured data

Object-relational database and reports server

Primary database model

Relational DBMS

Multivalue DBMS

Relational DBMS

Secondary database models

Document store

Time Series DBMS

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

Score	10.63
Rank	#40	Overall
	#24	Relational DBMS

Score	0.28
Rank	#291	Overall
	#10	Multivalue DBMS

Score	133.72
Rank	#7	Overall
	#5	Relational DBMS

Score	0.18
Rank	#313	Overall
	#140	Relational DBMS

Website

impala.apache.org

geospock.com

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

www.snowflake.com

www.valentina-db.net

Technical documentation

impala.apache.org/impala-docs.html

docs.snowflake.net/manuals/index.html

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

GeoSpock

Rocket Software, originally Martin Phillips

Snowflake Computing Inc.

Paradigma Software

Initial release

2013

1993

2014

1999

Current release

4.1.0, June 2022

2.0, September 2019

3.4-12

5.7.5

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

GPLv2, extended commercial license available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Java, Javascript

Server operating systems

Linux

hosted

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

hosted

Linux
OS X
Windows

Data scheme

yes

with some exceptions

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

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

temporal, categorical

yes

SQL

Support of SQL

SQL-like DML and DDL statements

ANSI SQL for query only (using Presto)

yes

APIs and other access methods

JDBC
ODBC

JDBC

CLI Client
JDBC
ODBC

ODBC

Supported programming languages

All languages supporting JDBC/ODBC

.Net
Basic
C
Java
Objective C
PHP
Python

JavaScript (Node.js)
Python

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

user defined functions

yes

Triggers

yes

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

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

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

Access rights for users can be defined per table

Access rights can be defined down to the item level

Users with fine-grained authorization concept, user roles and pluggable authentication

fine grained access rights according to SQL-standard

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