DBMS > Amazon Redshift vs. Prometheus vs. Transwarp Hippo vs. Warp 10

System Properties Comparison Amazon Redshift vs. Prometheus vs. Transwarp Hippo 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

Open-source Time Series DBMS and monitoring system

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

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

Primary database model

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	8.42
Rank	#47	Overall
	#2	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#13	Vector DBMS

Score	0.07
Rank	#349	Overall
	#32	Time Series DBMS

Website

aws.amazon.com/redshift

prometheus.io

www.transwarp.cn/en/subproduct/hippo

www.warp10.io

Technical documentation

docs.aws.amazon.com/redshift

prometheus.io/docs

www.warp10.io/content/02_Getting_started

Developer

Amazon (based on PostgreSQL)

SenX

Initial release

2012

2015

2023

2015

Current release

1.0, May 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

Apache License 2.0

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

Server operating systems

hosted

Linux
Windows

Linux
macOS

Linux
OS X
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data only

Vector, Numeric and String

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.

Import of XML data possible

Secondary indexes

restricted

SQL

Support of SQL

yes

does not fully support an SQL-standard

APIs and other access methods

JDBC
ODBC

RESTful HTTP/JSON API

RESTful HTTP API

HTTP API
Jupyter
WebSocket

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

C++
Java
Python

Server-side scripts

Stored procedures

user defined functions

in Python

yes

WarpScript

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by Federation

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

none

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

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

Role based access control and fine grained access rights

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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