DBMS > Apache Impala vs. RDFox vs. SAP IQ vs. Snowflake vs. VoltDB

System Properties Comparison Apache Impala vs. RDFox vs. SAP IQ vs. Snowflake vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

High performance knowledge graph and semantic reasoning engine

Columnar RDBMS optimized for Big Data analytics

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

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

column-oriented

Secondary database models

Document store

Relational DBMS

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	0.23
Rank	#308	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	2.75
Rank	#104	Overall
	#53	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

impala.apache.org

www.oxfordsemantic.tech

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

www.snowflake.com

www.voltdb.com

Technical documentation

impala.apache.org/impala-docs.html

docs.oxfordsemantic.tech

help.sap.com/docs/SAP_IQ

docs.snowflake.net/manuals/index.html

docs.voltdb.com

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Oxford Semantic Technologies

SAP, formerly Sybase

Snowflake Computing Inc.

VoltDB Inc.

Initial release

2013

2017

1994

2014

2010

Current release

4.1.0, June 2022

6.0, Septermber 2022

16.1 SPS04, April 2019

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java, C++

Server operating systems

Linux

Linux
macOS
Windows

AIX
HP-UX
Linux
Solaris
Windows

hosted

Linux
OS X

for development

Data scheme

yes

RDF schemas

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

SQL

Support of SQL

SQL-like DML and DDL statements

yes

only a subset of SQL 99

APIs and other access methods

JDBC
ODBC

RESTful HTTP API
SPARQL 1.1

ADO.NET
JDBC
ODBC
RESTful HTTP API

CLI Client
JDBC
ODBC

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

All languages supporting JDBC/ODBC

C
Java

C
C#
C++
Java
Perl
PHP
Python
Ruby

JavaScript (Node.js)
Python

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

user defined functions

Java

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

shared disk or shared nothing architectures with SAP IQ Multiplexer

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

replication via a shared file system

SAP/Sybase Replication Server

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups

Immediate Consistency

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

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

Roles, resources, and access types

fine grained access rights according to SQL-standard

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

Users and roles with access to stored procedures

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