DBMS > Splunk vs. Tarantool vs. Tkrzw vs. Transwarp Hippo

System Properties Comparison Splunk vs. Tarantool vs. Tkrzw vs. Transwarp Hippo

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Editorial information provided by DB-Engines

Name

Description

Analytics Platform for Big Data

In-memory computing platform with a flexible data schema for efficiently building high-performance applications

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

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

Primary database model

Search engine

Document store
Key-value store
Relational DBMS

Key-value store

Vector DBMS

Secondary database models

Spatial DBMS

with Tarantool/GIS extension

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

Score	89.10
Rank	#14	Overall
	#2	Search engines

Score	1.67
Rank	#143	Overall
	#25	Document stores
	#25	Key-value stores
	#65	Relational DBMS

Score	0.07
Rank	#372	Overall
	#57	Key-value stores

Score	0.05
Rank	#386	Overall
	#14	Vector DBMS

Website

www.splunk.com

www.tarantool.io

dbmx.net/tkrzw

www.transwarp.cn/en/subproduct/hippo

Technical documentation

docs.splunk.com/Documentation/Splunk

www.tarantool.io/en/doc

Developer

Splunk Inc.

Mikio Hirabayashi

Initial release

2003

2008

2020

2023

Current release

2.10.0, May 2022

0.9.3, August 2020

1.0, May 2023

License

Commercial or Open Source

commercial

Limited free edition and free developer edition available

Open Source

BSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise

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 and C++

C++

Server operating systems

Linux
OS X
Solaris
Windows

BSD
Linux
macOS

Linux
macOS

Data scheme

yes

Flexible data schema: relational definition for tables with ability to store json-like documents in columns

schema-free

Typing

predefined data types such as float or date

yes

string, double, decimal, uuid, integer, blob, boolean, datetime

Vector, Numeric and String

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

Full-featured ANSI SQL support

APIs and other access methods

HTTP REST

Open binary protocol

RESTful HTTP API

Supported programming languages

C#
Java
JavaScript
PHP
Python
Ruby

C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust

C++
Java
Python
Ruby

C++
Java
Python

Server-side scripts

Stored procedures

yes

Lua, C and SQL stored procedures

Triggers

yes

yes, before/after data modification events, on replication events, client session events

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Asynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Casual consistency across sharding partitions
Eventual consistency within replicaset partition

when using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition

when using Raft

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, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions

Concurrency

Support for concurrent manipulation of data

yes

yes, cooperative multitasking

yes

Durability

Support for making data persistent

yes

yes, write ahead logging

yes

In-memory capabilities

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

yes, full featured in-memory storage engine with persistence

yes

using specific database classes

yes

User concepts

Access control

Access rights for users and roles

Access Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

Role based access control and fine grained access rights

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More resources

DB-Engines blog posts

Enterprise Search Engines almost double their popularity in the last 12 months
2 July 2014, Paul Andlinger

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Data processing speed and reliability: in-memory synchronous replication
9 November 2021, Vladimir Perepelytsya, Tarantool (sponsor)

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