DBMS > Apache Druid vs. Cachelot.io vs. LevelDB vs. SWC-DB vs. Yanza

System Properties Comparison Apache Druid vs. Cachelot.io vs. LevelDB 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

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

In-memory caching system

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

A high performance, scalable Wide Column DBMS

Time Series DBMS for IoT Applications

Primary database model

Relational DBMS
Time Series DBMS

Key-value store

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	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

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

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

druid.apache.org

cachelot.io

github.com/google/leveldb

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

yanza.com

Technical documentation

druid.apache.org/docs/latest/design

github.com/google/leveldb/blob/main/doc/index.md

Developer

Apache Software Foundation and contributors

Google

Alex Kashirin

Yanza

Initial release

2012

2015

2011

2020

2015

Current release

29.0.1, April 2024

1.23, February 2021

0.5, April 2021

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Simplified BSD License

Open Source

BSD

Open Source

GPL V3

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

Java

C++

Server operating systems

Linux
OS X
Unix

FreeBSD
Linux
OS X

Illumos
Linux
OS X
Windows

Linux

Windows

Data scheme

yes

schema-less columns are supported

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

yes

SQL

Support of SQL

SQL for querying

SQL-like query language

APIs and other access methods

JDBC
RESTful HTTP/JSON API

Memcached protocol

Proprietary protocol
Thrift

HTTP API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

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

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

C++

any language that supports HTTP calls

Server-side scripts

Stored procedures

Triggers

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

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

with automatic compression on writes

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

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