DBMS > HarperDB vs. JanusGraph vs. Microsoft Azure Cosmos DB vs. Microsoft Azure Table Storage

System Properties Comparison HarperDB vs. JanusGraph vs. Microsoft Azure Cosmos DB vs. Microsoft Azure Table Storage

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Editorial information provided by DB-Engines

Name

Description

HarperDB takes the "stack" out of "tech stack" by combining an ultra-fast document-style data store, in-memory cache, real-time message broker, and your application components into a single distributed technology.

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

Globally distributed, horizontally scalable, multi-model database service

A Wide Column Store for rapid development using massive semi-structured datasets

Primary database model

Document store

Graph DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Wide column store

Secondary database models

Spatial DBMS

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

Score	0.55
Rank	#243	Overall
	#38	Document stores

Score	1.85
Rank	#134	Overall
	#12	Graph DBMS

Score	24.97
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	3.55
Rank	#80	Overall
	#6	Wide column stores

Website

www.harperdb.io

janusgraph.org

azure.microsoft.com/services/cosmos-db

azure.microsoft.com/en-us/services/storage/tables

Technical documentation

docs.harperdb.io/docs

docs.janusgraph.org

learn.microsoft.com/azure/cosmos-db

Developer

HarperDB

Linux Foundation; originally developed as Titan by Aurelius

Microsoft

Initial release

2017

2014

2012

Current release

3.1, August 2021

1.0.0, October 2023

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache 2.0

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

Node.js

Java

Server operating systems

Linux
OS X

Linux
OS X
Unix
Windows

hosted

Data scheme

dynamic schema

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON data types

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.

Secondary indexes

yes

All properties auto-indexed by default

SQL

Support of SQL

SQL-like data manipulation statements

SQL-like query language

APIs and other access methods

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

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

RESTful HTTP API

Supported programming languages

.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

Clojure
Java
Python

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

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

Custom Functions

since release 3.1

yes

JavaScript

Triggers

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

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

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Sharding

Implicit feature of the cloud service

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

yes

the nodes on which a table resides can be defined

yes

Implicit feature of the cloud service

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

Atomic execution of specific operations

ACID

Multi-item ACID transactions with snapshot isolation within a partition

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes, using LMDB

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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

User authentification and security via Rexster Graph Server

Access rights can be defined down to the item level

Access rights based on private key authentication or shared access signatures

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