DBMS > BoltDB vs. Datomic vs. Lovefield vs. Microsoft Azure Cosmos DB vs. Splunk

System Properties Comparison BoltDB vs. Datomic vs. Lovefield vs. Microsoft Azure Cosmos DB vs. Splunk

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

Globally distributed, horizontally scalable, multi-model database service

Analytics Platform for Big Data

Primary database model

Key-value store

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Search engine

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	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	86.45
Rank	#14	Overall
	#2	Search engines

Website

github.com/boltdb/bolt

www.datomic.com

google.github.io/lovefield

azure.microsoft.com/services/cosmos-db

www.splunk.com

Technical documentation

docs.datomic.com

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

learn.microsoft.com/azure/cosmos-db

docs.splunk.com/Documentation/Splunk

Developer

Cognitect

Google

Microsoft

Splunk Inc.

Initial release

2013

2012

2014

2003

Current release

1.0.6735, June 2023

2.1.12, February 2017

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

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

Java, Clojure

JavaScript

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

hosted

Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

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 properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

SQL-like query language

Splunk Search Processing Language for search commands

APIs and other access methods

RESTful HTTP API

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

HTTP REST

Supported programming languages

Clojure
Java

JavaScript

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Transaction Functions

JavaScript

yes

Triggers

By using transaction functions

Using read-only observers

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

none

Sharding

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

none

yes

Implicit feature of the cloud service

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Multi-item ACID transactions with snapshot isolation within a partition

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

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

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

yes

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 can be defined down to the item level

Access rights for users and roles

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