DBMS > Hive vs. MySQL vs. Prometheus vs. Quasardb vs. RisingWave

System Properties Comparison Hive vs. MySQL vs. Prometheus vs. Quasardb vs. RisingWave

Editorial information provided by DB-Engines

Name

Description

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Widely used open source RDBMS

Open-source Time Series DBMS and monitoring system

Distributed, high-performance timeseries database

A distributed RDBMS for stream processing, wire-compatible with PostgreSQL

Primary database model

Relational DBMS

Key/Value like access via memcached API

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	8.42
Rank	#47	Overall
	#2	Time Series DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	0.58
Rank	#242	Overall
	#111	Relational DBMS

Website

www.risingwave.com/database

Technical documentation

cwiki.apache.org/confluence/display/Hive/Home

dev.mysql.com/doc

prometheus.io/docs

doc.quasar.ai/master

docs.risingwave.com/docs/current/intro

Developer

Apache Software Foundation

initially developed by Facebook

Oracle

since 2010, originally MySQL AB, then Sun

quasardb

RisingWave Labs

Initial release

2012

1995

2015

2009

2022

Current release

3.1.3, April 2022

8.4.0, April 2024

3.14.1, January 2024

1.2, September 2023

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache 2.0

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C and C++

C++

Rust

Server operating systems

All OS with a Java VM

FreeBSD
Linux
OS X
Solaris
Windows

Linux
Windows

BSD
Linux
OS X
Windows

Docker
Linux
macOS

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data only

yes

integer and binary

Standard SQL-types and JSON

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

Import of XML data possible

Secondary indexes

yes

with tags

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

with proprietary extensions

SQL-like query language

yes

APIs and other access methods

JDBC
ODBC
Thrift

ADO.NET
JDBC
ODBC
Proprietary native API

RESTful HTTP/JSON API

HTTP API

JDBC
PostgreSQL wire protocol

Supported programming languages

C++
Java
PHP
Python

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

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

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

proprietary syntax

UDFs in Python or Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication
Source-replica replication

yes

by Federation

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

by using LevelDB

yes

In-memory capabilities

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

yes

Transient mode

yes

User concepts

Access control

Access rights for users, groups and roles

Users with fine-grained authorization concept

no user groups or roles

Cryptographically strong user authentication and audit trail

Users and Roles

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