DBMS > BoltDB vs. Datomic vs. Lovefield vs. Splunk vs. VoltDB

System Properties Comparison BoltDB vs. Datomic vs. Lovefield vs. Splunk vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

An embedded key-value store for Go.

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Embeddable relational database for web apps written in pure JavaScript

Analytics Platform for Big Data

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

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

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

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	86.45
Rank	#14	Overall
	#2	Search engines

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

github.com/boltdb/bolt

www.datomic.com

google.github.io/lovefield

www.splunk.com

www.voltdb.com

Technical documentation

docs.datomic.com

github.com/google/lovefield/blob/master/docs/spec_index.md

docs.splunk.com/Documentation/Splunk

docs.voltdb.com

Developer

Cognitect

Google

Splunk Inc.

VoltDB Inc.

Initial release

2013

2012

2014

2003

2010

Current release

1.0.6735, June 2023

2.1.12, February 2017

11.3, April 2022

License

Commercial or Open Source

Open Source

MIT License

commercial

limited edition free

Open Source

Apache 2.0

commercial

Limited free edition and free developer edition available

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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, Clojure

JavaScript

Java, C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux
OS X
Solaris
Windows

Linux
OS X

for development

Data scheme

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

SQL-like query language

via JavaScript builder pattern

Splunk Search Processing Language for search commands

yes

only a subset of SQL 99

APIs and other access methods

RESTful HTTP API

HTTP REST

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

Clojure
Java

JavaScript

C#
Java
JavaScript
PHP
Python
Ruby

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

Java

Triggers

By using transaction functions

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

none

Multi-source replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

yes

ACID

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

Snapshots and command logging

In-memory capabilities

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

yes

recommended only for testing and development

yes

using MemoryDB

User concepts

Access control

Access rights for users and roles

Users and roles with access to stored procedures

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