DBMS > Amazon Redshift vs. HBase vs. IBM Db2 Event Store vs. TempoIQ vs. ToroDB

System Properties Comparison Amazon Redshift vs. HBase vs. IBM Db2 Event Store vs. TempoIQ vs. ToroDB

Editorial information provided by DB-Engines

Name

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Large scale data warehouse service for use with business intelligence tools

Wide-column store based on Apache Hadoop and on concepts of BigTable

Distributed Event Store optimized for Internet of Things use cases

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Relational DBMS

Wide column store

Event Store
Time Series DBMS

Time Series DBMS

Document store

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	27.97
Rank	#26	Overall
	#2	Wide column stores

Score	0.27
Rank	#309	Overall
	#2	Event Stores
	#28	Time Series DBMS

Website

aws.amazon.com/redshift

hbase.apache.org

www.ibm.com/products/db2-event-store

tempoiq.com (offline)

github.com/torodb/server

Technical documentation

docs.aws.amazon.com/redshift

hbase.apache.org/book.html

www.ibm.com/docs/en/db2-event-store

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

Apache top-level project, originally developed by Powerset

IBM

TempoIQ

8Kdata

Initial release

2012

2008

2017

2012

2016

Current release

2.3.4, January 2021

2.0

License

Commercial or Open Source

commercial

Open Source

Apache version 2

commercial

free developer edition available

commercial

Open Source

AGPL-V3

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

Java

C and C++

Java

Server operating systems

hosted

Linux
Unix
Windows

using Cygwin

Linux

Linux, macOS, Windows for the developer addition

All OS with a Java 7 VM

Data scheme

yes

schema-free, schema definition possible

yes

schema-free

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

yes

string, integer, double, boolean, date, object_id

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.

Secondary indexes

restricted

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

through the embedded Spark runtime

APIs and other access methods

JDBC
ODBC

Java API
RESTful HTTP API
Thrift

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Groovy
Java
PHP
Python
Scala

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Coprocessors in Java

yes

Triggers

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

Active-active shard replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency

Eventual Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

Transaction concepts

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

ACID

Single row ACID (across millions of columns)

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

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

fine grained access rights according to SQL-standard

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

fine grained access rights according to SQL-standard

simple authentication-based access control

Access rights for users and roles

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