DBMS > Cachelot.io vs. Hive vs. Snowflake vs. Yanza

System Properties Comparison Cachelot.io vs. Hive vs. Snowflake vs. Yanza

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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

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

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

Time Series DBMS for IoT Applications

Primary database model

Key-value store

Relational DBMS

Time Series DBMS

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

Score	0.04
Rank	#388	Overall
	#62	Key-value stores

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

cachelot.io

hive.apache.org

www.snowflake.com

yanza.com

Technical documentation

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

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation

initially developed by Facebook

Snowflake Computing Inc.

Yanza

Initial release

2015

2012

2014

2015

Current release

3.1.3, April 2022

License

Commercial or Open Source

Open Source

Simplified BSD License

Open Source

Apache Version 2

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++

Java

Server operating systems

FreeBSD
Linux
OS X

All OS with a Java VM

hosted

Windows

Data scheme

schema-free

yes

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

schema-free

Typing

predefined data types such as float or date

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

SQL-like DML and DDL statements

yes

APIs and other access methods

Memcached protocol

JDBC
ODBC
Thrift

CLI Client
JDBC
ODBC

HTTP API

Supported programming languages

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

C++
Java
PHP
Python

JavaScript (Node.js)
Python

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

user defined functions

Triggers

similar concept for controling cloud resources

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

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.

User concepts

Access control

Access rights for users, groups and roles

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

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