DBMS > Amazon DynamoDB vs. LokiJS vs. Microsoft Access vs. Oracle Berkeley DB vs. Splunk

System Properties Comparison Amazon DynamoDB vs. LokiJS vs. Microsoft Access vs. Oracle Berkeley DB vs. Splunk

Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

In-memory JavaScript DBMS

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

Widely used in-process key-value store

Analytics Platform for Big Data

Primary database model

Document store
Key-value store

Document store

Relational DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Search engine

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

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	0.43
Rank	#264	Overall
	#42	Document stores

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Score	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Score	86.45
Rank	#14	Overall
	#2	Search engines

Website

aws.amazon.com/dynamodb

github.com/techfort/LokiJS

www.microsoft.com/en-us/microsoft-365/access

www.oracle.com/database/technologies/related/berkeleydb.html

www.splunk.com

Technical documentation

docs.aws.amazon.com/dynamodb

techfort.github.io/LokiJS

developer.microsoft.com/en-us/access

docs.oracle.com/cd/E17076_05/html/index.html

docs.splunk.com/Documentation/Splunk

Developer

Amazon

Microsoft

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Splunk Inc.

Initial release

2012

2014

1992

1994

2003

Current release

1902 (16.0.11328.20222), March 2019

18.1.40, May 2020

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

commercial

Bundled with Microsoft Office

Open Source

commercial license available

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

JavaScript

C++

C, Java, C++ (depending on the Berkeley DB edition)

Server operating systems

hosted

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

Windows

Not a real database server, but making use of DLLs

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

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

only with the Berkeley DB XML edition

yes

Secondary indexes

yes

via views

yes

SQL

Support of SQL

yes

but not compliant to any SQL standard

yes

SQL interfaced based on SQLite is available

Splunk Search Processing Language for search commands

APIs and other access methods

RESTful HTTP API

JavaScript API

ADO.NET
DAO
ODBC
OLE DB

HTTP REST

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

JavaScript

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

View functions in JavaScript

yes

since Access 2010 using the ACE-engine

yes

Triggers

yes

by integration with AWS Lambda

yes

since Access 2010 using the ACE-engine

yes

only for the SQL API

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Source-replica replication

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

none

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

atomic operations within a single collection possible

ACID

but no files for transaction logging

ACID

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

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

yes

but no files for transaction logging

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 rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

a simple user-level security was built in till version Access 2003

Access rights for users and roles

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