DBMS > Amazon Redshift vs. Apache Impala vs. InfinityDB vs. Sphinx vs. Tibero

System Properties Comparison Amazon Redshift vs. Apache Impala vs. InfinityDB vs. Sphinx vs. Tibero

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Analytic DBMS for Hadoop

A Java embedded Key-Value Store which extends the Java Map interface

Open source search engine for searching in data from different sources, e.g. relational databases

A secure RDBMS, designed for easy portability from Oracle

Primary database model

Secondary database models

Document store

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Score	17.94
Rank	#34	Overall
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Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	0.00
Rank	#378	Overall
	#57	Key-value stores

Score	5.98
Rank	#56	Overall
	#5	Search engines

Score	1.78
Rank	#140	Overall
	#64	Relational DBMS

Website

aws.amazon.com/redshift

impala.apache.org

boilerbay.com

sphinxsearch.com

us.tmaxsoft.com/products/tibero

Technical documentation

docs.aws.amazon.com/redshift

impala.apache.org/impala-docs.html

boilerbay.com/infinitydb/manual

sphinxsearch.com/docs

technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Boiler Bay Inc.

Sphinx Technologies Inc.

TmaxSoft

Initial release

2012

2013

2002

2001

2003

Current release

4.1.0, June 2022

4.0

3.5.1, February 2023

6, April 2015

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

commercial

Open Source

GPL version 2, commercial licence available

commercial

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++

C and Assembler

Server operating systems

hosted

Linux

All OS with a Java VM

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

yes

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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

restricted

yes

manual creation possible, using inversions based on multi-value capability

yes

full-text index on all search fields

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like DML and DDL statements

SQL-like query language (SphinxQL)

yes

APIs and other access methods

JDBC
ODBC

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

Proprietary protocol

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI

Supported programming languages

All languages supporting JDBC/ODBC

Java

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic

Server-side scripts

Stored procedures

user defined functions

in Python

yes

user defined functions and integration of map-reduce

Persistent Stored Procedure (PSM)

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Partitioning is done manually, search queries against distributed index is supported

horizontal partitioning

by range, hash, list or composite

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

Immediate Consistency

Eventual Consistency

Immediate Consistency

READ-COMMITTED or SERIALIZED

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

manual creation possible, using inversions based on multi-value capability

yes

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Sphinx index.

yes

In-memory capabilities

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

yes

planned for next version

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

fine grained access rights according to SQL-standard (SQL 92, SQL 99)

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