DBMS > atoti vs. Splunk vs. Tkrzw

System Properties Comparison atoti vs. Splunk vs. Tkrzw

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Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

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

Primary database model

Object oriented DBMS

Search engine

Key-value store

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

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	86.45
Rank	#14	Overall
	#2	Search engines

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

Website

atoti.io

www.splunk.com

dbmx.net/tkrzw

Technical documentation

docs.atoti.io

docs.splunk.com/Documentation/Splunk

Developer

ActiveViam

Splunk Inc.

Mikio Hirabayashi

Initial release

2003

2020

Current release

0.9.3, August 2020

License

Commercial or Open Source

commercial

free versions available

commercial

Limited free edition and free developer edition available

Open Source

Apache Version 2.0

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

Java

C++

Server operating systems

Linux
OS X
Solaris
Windows

Linux
macOS

Data scheme

yes

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

Multidimensional Expressions (MDX)

Splunk Search Processing Language for search commands

APIs and other access methods

HTTP REST

Supported programming languages

C#
Java
JavaScript
PHP
Python
Ruby

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

Python

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

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

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

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

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

User concepts

Access control

Access rights for users and roles

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More resources

DB-Engines blog posts

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2 July 2014, Paul Andlinger

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