DBMS > Cachelot.io vs. ReductStore vs. SWC-DB vs. Warp 10 vs. Yanza

System Properties Comparison Cachelot.io vs. ReductStore vs. SWC-DB vs. Warp 10 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

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

A high performance, scalable Wide Column DBMS

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Time Series DBMS for IoT Applications

Primary database model

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	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Score	0.07
Rank	#349	Overall
	#32	Time Series DBMS

Website

cachelot.io

github.com/reductstore
www.reduct.store

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

www.warp10.io

yanza.com

Technical documentation

www.reduct.store/docs

www.warp10.io/content/02_Getting_started

Developer

ReductStore LLC

Alex Kashirin

SenX

Yanza

Initial release

2015

2023

2020

2015

Current release

1.9, March 2024

0.5, April 2021

License

Commercial or Open Source

Open Source

Simplified BSD License

Open Source

Business Source License 1.1

Open Source

GPL V3

Open Source

Apache License 2.0

commercial

free version available

Cloud-based only

Only available as a cloud service

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++

C++, Rust

C++

Java

Server operating systems

FreeBSD
Linux
OS X

Docker
Linux
macOS
Windows

Linux

Linux
OS X
Windows

Windows

Data scheme

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.

Secondary indexes

SQL

Support of SQL

SQL-like query language

APIs and other access methods

Memcached protocol

HTTP API

Proprietary protocol
Thrift

HTTP API
Jupyter
WebSocket

HTTP API

Supported programming languages

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

C++
JavaScript (Node.js)
Python
Rust

C++

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes

WarpScript

Triggers

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on HBase

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

based on HBase

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

based on HBase

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

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

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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