DBMS > ReductStore vs. Splunk vs. Tkrzw vs. Yaacomo

System Properties Comparison ReductStore vs. Splunk vs. Tkrzw vs. Yaacomo

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Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

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.

Analytics Platform for Big Data

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

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

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	86.45
Rank	#14	Overall
	#2	Search engines

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

Website

github.com/reductstore
www.reduct.store

www.splunk.com

dbmx.net/tkrzw

yaacomo.com

Technical documentation

www.reduct.store/docs

docs.splunk.com/Documentation/Splunk

Developer

ReductStore LLC

Splunk Inc.

Mikio Hirabayashi

Q2WEB GmbH

Initial release

2023

2003

2020

2009

Current release

1.9, March 2024

0.9.3, August 2020

License

Commercial or Open Source

Open Source

Business Source License 1.1

commercial

Limited free edition and free developer edition available

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++, Rust

C++

Server operating systems

Docker
Linux
macOS
Windows

Linux
OS X
Solaris
Windows

Linux
macOS

Android
Linux
Windows

Data scheme

yes

schema-free

yes

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

Splunk Search Processing Language for search commands

yes

APIs and other access methods

HTTP API

HTTP REST

JDBC
ODBC

Supported programming languages

C++
JavaScript (Node.js)
Python
Rust

C#
Java
JavaScript
PHP
Python
Ruby

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

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

using specific database classes

yes

User concepts

Access control

Access rights for users and roles

fine grained access rights according to SQL-standard

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