DBMS > EXASOL vs. RisingWave vs. Snowflake vs. TerarkDB vs. Yanza

System Properties Comparison EXASOL vs. RisingWave vs. Snowflake vs. TerarkDB vs. Yanza

Editorial information provided by DB-Engines

Name

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

Description

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

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

Cloud-based data warehousing service for structured and semi-structured data

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Time Series DBMS for IoT Applications

Primary database model

Relational DBMS

Key-value store

Time Series DBMS

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

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	0.58
Rank	#242	Overall
	#111	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

www.exasol.com

www.risingwave.com/database

www.snowflake.com

github.com/bytedance/terarkdb

yanza.com

Technical documentation

www.exasol.com/resources

docs.risingwave.com/docs/current/intro

docs.snowflake.net/manuals/index.html

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Exasol

RisingWave Labs

Snowflake Computing Inc.

ByteDance, originally Terark

Yanza

Initial release

2000

2022

2014

2016

2015

Current release

1.2, September 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

restricted open source version available

commercial

free version available

Cloud-based only

Only available as a cloud service

yes

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Rust

C++

Server operating systems

Docker
Linux
macOS

hosted

Windows

Data scheme

yes

support of semi-structured data formats (JSON, XML, Avro)

schema-free

Typing

predefined data types such as float or date

yes

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

JDBC
PostgreSQL wire protocol

CLI Client
JDBC
ODBC

C++ API
Java API

HTTP API

Supported programming languages

Java
Lua
Python
R

Go
Java
JavaScript (Node.js)
Python

JavaScript (Node.js)
Python

C++
Java

any language that supports HTTP calls

Server-side scripts

Stored procedures

user defined functions

UDFs in Python or Java

user defined functions

Triggers

yes

similar concept for controling cloud resources

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

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

Access rights for users, groups and roles according to SQL-standard

Users and Roles

Users with fine-grained authorization concept, user roles and pluggable authentication

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