DBMS > Amazon DocumentDB vs. Blazegraph vs. Hawkular Metrics vs. LokiJS vs. Manticore Search

System Properties Comparison Amazon DocumentDB vs. Blazegraph vs. Hawkular Metrics vs. LokiJS vs. Manticore Search

Editorial information provided by DB-Engines

Name

Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.

Description

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

High-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

In-memory JavaScript DBMS

Multi-storage database for search, including full-text search.

Primary database model

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

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

Score	1.91
Rank	#132	Overall
	#24	Document stores

Score	0.75
Rank	#219	Overall
	#19	Graph DBMS
	#8	RDF stores

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	0.43
Rank	#264	Overall
	#42	Document stores

Score	0.22
Rank	#312	Overall
	#21	Search engines

Website

aws.amazon.com/documentdb

blazegraph.com

www.hawkular.org

github.com/techfort/LokiJS

manticoresearch.com

Technical documentation

aws.amazon.com/documentdb/resources

wiki.blazegraph.com

www.hawkular.org/hawkular-metrics/docs/user-guide

techfort.github.io/LokiJS

manual.manticoresearch.com

Developer

Blazegraph

Community supported by Red Hat

Manticore Software

Initial release

2019

2006

2014

2017

Current release

2.1.5, March 2019

6.0, February 2023

License

Commercial or Open Source

commercial

Open Source

extended commercial license available

Open Source

Apache 2.0

Open Source

GPL version 2

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

JavaScript

C++

Server operating systems

hosted

Linux
OS X
Windows

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

FreeBSD
Linux
macOS
Windows

Data scheme

schema-free

Fixed schema

Typing

predefined data types such as float or date

yes

RDF literal types

yes

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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.

Can index from XML

Secondary indexes

yes

via views

yes

full-text index on all search fields

SQL

Support of SQL

SPARQL is used as query language

SQL-like query language

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

HTTP REST

JavaScript API

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

Go
Java
Python
Ruby

JavaScript

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

Server-side scripts

Stored procedures

yes

View functions in JavaScript

user defined functions

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

none

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes

selectable replication factor

based on Cassandra

none

Synchronous replication based on Galera library

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

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

none

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

atomic operations within a single collection possible

yes

isolated transactions for atomic changes and binary logging for safe writes

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

The original contents of fields are not stored in the Manticore index.

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

Security and Authentication via Web Application Container (Tomcat, Jetty)

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More resources

DB-Engines blog posts

New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

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