DBMS > BoltDB vs. Elasticsearch vs. Riak KV vs. Splunk vs. SQLite

System Properties Comparison BoltDB vs. Elasticsearch vs. Riak KV vs. Splunk vs. SQLite

Editorial information provided by DB-Engines

Name

Description

An embedded key-value store for Go.

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

Distributed, fault tolerant key-value store

Analytics Platform for Big Data

Widely used embeddable, in-process RDBMS

Primary database model

Key-value store

Search engine

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Search engine

Relational DBMS

Secondary database models

Document store
Spatial DBMS
Vector DBMS

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

Score	0.74
Rank	#220	Overall
	#31	Key-value stores

Score	135.35
Rank	#7	Overall
	#1	Search engines

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Score	86.45
Rank	#14	Overall
	#2	Search engines

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

github.com/boltdb/bolt

www.elastic.co/elasticsearch

www.splunk.com

www.sqlite.org

Technical documentation

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

www.tiot.jp/riak-docs/riak/kv/latest

docs.splunk.com/Documentation/Splunk

www.sqlite.org/docs.html

Developer

Elastic

OpenSource, formerly Basho Technologies

Splunk Inc.

Dwayne Richard Hipp

Initial release

2013

2010

2009

2003

2000

Current release

8.6, January 2023

3.2.0, December 2022

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

Open Source

MIT License

Open Source

Elastic License

Open Source

Apache version 2, commercial enterprise edition

commercial

Limited free edition and free developer edition available

Open Source

Public Domain

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

Erlang

Server operating systems

BSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

Linux
OS X

Linux
OS X
Solaris
Windows

server-less

Data scheme

schema-free

Flexible type definitions. Once a type is defined, it is persistent

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

All search fields are automatically indexed

restricted

yes

SQL

Support of SQL

SQL-like query language

Splunk Search Processing Language for search commands

yes

SQL-92 is not fully supported

APIs and other access methods

Java API
RESTful HTTP/JSON API

HTTP API
Native Erlang Interface

HTTP REST

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

C#
Java
JavaScript
PHP
Python
Ruby

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

Erlang

yes

Triggers

yes

by using the 'percolation' feature

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

no "single point of failure"

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

selectable replication factor

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Eventual Consistency

Foreign keys

Referential integrity

links between data sets can be stored

yes

Transaction concepts

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

yes

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

via file-system locks

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.

Memcached and Redis integration

yes

User concepts

Access control

yes, using Riak Security

Access rights for users and roles

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