DBMS > Cachelot.io vs. Databricks vs. openGemini vs. SWC-DB vs. Yanza

System Properties Comparison Cachelot.io vs. Databricks vs. openGemini vs. SWC-DB vs. Yanza

Editorial information provided by DB-Engines

Name

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

Description

In-memory caching system

The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.

An open source distributed Time Series DBMS with high concurrency, high performance, and high scalability

A high performance, scalable Wide Column DBMS

Time Series DBMS for IoT Applications

Primary database model

Key-value store

Document store
Relational DBMS

Time Series DBMS

Wide column store

Time Series DBMS

Secondary database models

Time Series DBMS

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

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

Score	78.61
Rank	#15	Overall
	#2	Document stores
	#10	Relational DBMS

Score	0.01
Rank	#375	Overall
	#39	Time Series DBMS

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

cachelot.io

www.databricks.com

www.opengemini.org
github.com/openGemini

github.com/kashirin-alex/swc-db
www.swcdb.org

yanza.com

Technical documentation

docs.databricks.com

docs.opengemini.org/guide

Developer

Databricks

Huawei and openGemini community

Alex Kashirin

Yanza

Initial release

2015

2013

2022

2020

2015

Current release

1.1, July 2023

0.5, April 2021

License

Commercial or Open Source

Open Source

Simplified BSD License

commercial

Open Source

Apache Version 2.0

Open Source

GPL V3

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

C++

Server operating systems

FreeBSD
Linux
OS X

hosted

Linux
Windows

Linux

Windows

Data scheme

schema-free

Flexible Schema (defined schema, partial schema, schema free)

schema-free

Typing

predefined data types such as float or date

Integer, Float, Boolean, String

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

with Databricks SQL

SQL-like query language

APIs and other access methods

Memcached protocol

JDBC
ODBC
RESTful HTTP API

HTTP REST

Proprietary protocol
Thrift

HTTP API

Supported programming languages

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

Python
R
Scala

C
C++
Go
Java
JavaScript (Node.js)
Python
Rust

C++

any language that supports HTTP calls

Server-side scripts

Stored procedures

user defined functions and aggregates

Triggers

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

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

Administrators and common users accounts

More information provided by the system vendor

Specific characteristics

Supported database models : In addition to the Document store and Relational DBMS...
» more

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