DBMS > BoltDB vs. Google BigQuery vs. RocksDB vs. Solr vs. Splunk

System Properties Comparison BoltDB vs. Google BigQuery vs. RocksDB vs. Solr vs. Splunk

Editorial information provided by DB-Engines

Name

Description

An embedded key-value store for Go.

Large scale data warehouse service with append-only tables

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

A widely used distributed, scalable search engine based on Apache Lucene

Analytics Platform for Big Data

Primary database model

Secondary database models

Spatial DBMS

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

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

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	42.91
Rank	#24	Overall
	#3	Search engines

Score	86.45
Rank	#14	Overall
	#2	Search engines

Website

github.com/boltdb/bolt

cloud.google.com/bigquery

rocksdb.org

solr.apache.org

www.splunk.com

Technical documentation

cloud.google.com/bigquery/docs

github.com/facebook/rocksdb/wiki

solr.apache.org/resources.html

docs.splunk.com/Documentation/Splunk

Developer

Google

Facebook, Inc.

Apache Software Foundation

Splunk Inc.

Initial release

2013

2010

2013

2006

2003

Current release

8.11.4, April 2024

9.6.0, April 2024

License

Commercial or Open Source

Open Source

MIT License

commercial

Open Source

BSD

Open Source

Apache Version 2

commercial

Limited free edition and free developer edition available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Java

Server operating systems

BSD
Linux
OS X
Solaris
Windows

hosted

Linux

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

schema-free

yes

Dynamic Fields enables on-the-fly addition of new fields

yes

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

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

All search fields are automatically indexed

yes

SQL

Support of SQL

yes

Solr Parallel SQL Interface

Splunk Search Processing Language for search commands

APIs and other access methods

RESTful HTTP/JSON API

C++ API
Java API

Java API
RESTful HTTP/JSON API

HTTP REST

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C++
Go
Java
Perl
Python
Ruby

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Java plugins

yes

Triggers

yes

User configurable commands triggered on index changes

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

Since BigQuery is designed for querying data

yes

optimistic locking

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

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

User concepts

Access control

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

yes

Access rights for users and roles

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