DBMS > Amazon DocumentDB vs. EsgynDB vs. Lovefield vs. Splunk vs. Stardog

System Properties Comparison Amazon DocumentDB vs. EsgynDB vs. Lovefield vs. Splunk vs. Stardog

Editorial information provided by DB-Engines

Name

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Embeddable relational database for web apps written in pure JavaScript

Analytics Platform for Big Data

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

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

Score	1.91
Rank	#131	Overall
	#24	Document stores

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	89.10
Rank	#14	Overall
	#2	Search engines

Score	2.07
Rank	#122	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

aws.amazon.com/documentdb

www.esgyn.cn

google.github.io/lovefield

www.splunk.com

www.stardog.com

Technical documentation

aws.amazon.com/documentdb/resources

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

docs.splunk.com/Documentation/Splunk

docs.stardog.com

Developer

Esgyn

Google

Splunk Inc.

Stardog-Union

Initial release

2019

2015

2014

2003

2010

Current release

2.1.12, February 2017

7.3.0, May 2020

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Limited free edition and free developer edition available

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

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

JavaScript

Java

Server operating systems

hosted

Linux

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

tested with Chrome, Firefox, IE, Safari

Linux
OS X
Solaris
Windows

Linux
macOS
Windows

Data scheme

schema-free

yes

schema-free and OWL/RDFS-schema support

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

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

Splunk Search Processing Language for search commands

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

ADO.NET
JDBC
ODBC

HTTP REST

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

All languages supporting JDBC/ODBC/ADO.Net

JavaScript

C#
Java
JavaScript
PHP
Python
Ruby

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

Java Stored Procedures

yes

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

Using read-only observers

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

Multi-source replication between multi datacenters

none

Multi-source replication

Multi-source replication in HA-Cluster

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

Immediate Consistency

Eventual Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

relationships in graphs

Transaction concepts

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

Atomic single-document operations

ACID

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

Durability

Support for making data persistent

yes

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

using MemoryDB

yes

User concepts

Access control

Access rights for users and roles

fine grained access rights according to SQL-standard

Access rights for users and roles

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More resources

DB-Engines blog posts

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