DBMS > RisingWave vs. Transwarp KunDB vs. Yaacomo

System Properties Comparison RisingWave vs. Transwarp KunDB vs. Yaacomo

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Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

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

OLTP DBMS based on a distributed architecture and highly compatible with MySQL and Oracle

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Relational DBMS

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

Score	0.58
Rank	#242	Overall
	#111	Relational DBMS

Score	0.10
Rank	#344	Overall
	#151	Relational DBMS

Website

www.risingwave.com/database

www.transwarp.cn/en/product/kundb

yaacomo.com

Technical documentation

docs.risingwave.com/docs/current/intro

Developer

RisingWave Labs

Transwarp

Q2WEB GmbH

Initial release

2022

2009

Current release

1.2, September 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Rust

Server operating systems

Docker
Linux
macOS

Android
Linux
Windows

Data scheme

yes

Typing

predefined data types such as float or date

Standard SQL-types and JSON

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

yes

SQL

Support of SQL

yes

APIs and other access methods

JDBC
PostgreSQL wire protocol

JDBC
ODBC

Supported programming languages

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

UDFs in Python or Java

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

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

Users and Roles

yes

fine grained access rights according to SQL-standard

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More resources

Recent citations in the news

Streaming Databases: Embracing the Convergence of Stream Processing and Databases
17 May 2024, InfoQ.com

RisingWave Cloud Democratizes Event Stream Processing, Making It Affordable at Cloud Scale
27 June 2023, Datanami

Ibis 8 Adds Streaming
5 March 2024, iProgrammer

Building a Formula 1 Streaming Data Pipeline With Kafka and Risingwave
5 September 2023, KDnuggets

Open Source Ibis 8.0 Lets Data Teams Write Code Once and Use Across Local, Batch and Streaming Query Engines ...
12 February 2024, GlobeNewswire

provided by Google News

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