DBMS > Amazon Redshift vs. Tigris vs. Tkrzw vs. Warp 10

System Properties Comparison Amazon Redshift vs. Tigris vs. Tkrzw vs. Warp 10

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

A horizontally scalable, ACID transactional, document database available both as a fully managed cloud service and for deployment on self-managed infrastructure

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Relational DBMS

Document store
Key-value store
Search engine
Time Series DBMS

Key-value store

Time Series DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	0.09
Rank	#363	Overall
	#49	Document stores
	#54	Key-value stores
	#22	Search engines
	#38	Time Series DBMS

Score	0.07
Rank	#372	Overall
	#57	Key-value stores

Score	0.14
Rank	#344	Overall
	#32	Time Series DBMS

Website

aws.amazon.com/redshift

www.tigrisdata.com

dbmx.net/tkrzw

www.warp10.io

Technical documentation

docs.aws.amazon.com/redshift

www.tigrisdata.com/docs

www.warp10.io/content/02_Getting_started

Developer

Amazon (based on PostgreSQL)

Tigris Data, Inc.

Mikio Hirabayashi

SenX

Initial release

2012

2022

2020

2015

Current release

0.9.3, August 2020

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

Open Source

Apache License 2.0

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

Server operating systems

hosted

Linux
macOS
Windows

Linux
macOS

Linux
OS X
Windows

Data scheme

yes

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.

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

APIs and other access methods

JDBC
ODBC

CLI Client
gRPC
RESTful HTTP API

HTTP API
Jupyter
WebSocket

Supported programming languages

All languages supporting JDBC/ODBC

Go
Java
JavaScript (Node.js)

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in Python

yes

WarpScript

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

based on HBase

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using FoundationDB

yes

In-memory capabilities

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

yes

using specific database classes

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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