DBMS > Blazegraph vs. Graphite vs. HarperDB vs. Microsoft Azure Cosmos DB

System Properties Comparison Blazegraph vs. Graphite vs. HarperDB vs. Microsoft Azure Cosmos DB

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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

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

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

Globally distributed, horizontally scalable, multi-model database service

Primary database model

Graph DBMS
RDF store

Time Series DBMS

Document store

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Spatial DBMS

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

Score	0.81
Rank	#213	Overall
	#19	Graph DBMS
	#8	RDF stores

Score	4.83
Rank	#67	Overall
	#4	Time Series DBMS

Score	0.60
Rank	#244	Overall
	#38	Document stores

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Website

blazegraph.com

github.com/graphite-project/graphite-web

www.harperdb.io

azure.microsoft.com/services/cosmos-db

Technical documentation

wiki.blazegraph.com

graphite.readthedocs.io

docs.harperdb.io/docs

learn.microsoft.com/azure/cosmos-db

Developer

Blazegraph

Chris Davis

HarperDB

Microsoft

Initial release

2006

2017

2014

Current release

2.1.5, March 2019

3.1, August 2021

License

Commercial or Open Source

Open Source

extended commercial license available

Open Source

Apache 2.0

commercial

free community edition available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Python

Node.js

Server operating systems

Linux
OS X
Windows

Linux
Unix

Linux
OS X

hosted

Data scheme

schema-free

yes

dynamic schema

schema-free

Typing

predefined data types such as float or date

yes

RDF literal types

Numeric data only

yes

JSON data types

yes

JSON types

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.

Secondary indexes

yes

All properties auto-indexed by default

SQL

Support of SQL

SPARQL is used as query language

SQL-like data manipulation statements

SQL-like query language

APIs and other access methods

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

HTTP API
Sockets

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

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

Supported programming languages

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

JavaScript (Node.js)
Python

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

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

Server-side scripts

Stored procedures

yes

Custom Functions

since release 3.1

JavaScript

Triggers

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

A table resides as a whole on one (or more) nodes in a cluster

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes

the nodes on which a table resides can be defined

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

none

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

yes

Relationships in Graphs

Transaction concepts

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

ACID

Atomic execution of specific operations

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

yes

locking

yes

Durability

Support for making data persistent

yes

yes, using LMDB

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

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

Access rights for users and roles

Access rights can be defined down to the item level

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