DBMS > Dgraph vs. HarperDB vs. Hazelcast vs. Microsoft Azure Cosmos DB vs. Valentina Server

System Properties Comparison Dgraph vs. HarperDB vs. Hazelcast vs. Microsoft Azure Cosmos DB vs. Valentina Server

Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

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.

A widely adopted in-memory data grid

Globally distributed, horizontally scalable, multi-model database service

Object-relational database and reports server

Primary database model

Graph DBMS

Document store

Key-value store

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

Document store

JSON support with IMDG 3.12

Spatial DBMS

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

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	0.55
Rank	#248	Overall
	#38	Document stores

Score	5.97
Rank	#57	Overall
	#6	Key-value stores

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.17
Rank	#327	Overall
	#145	Relational DBMS

Website

dgraph.io

www.harperdb.io

hazelcast.com

azure.microsoft.com/services/cosmos-db

www.valentina-db.net

Technical documentation

dgraph.io/docs

docs.harperdb.io/docs

hazelcast.org/imdg/docs

learn.microsoft.com/azure/cosmos-db

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Dgraph Labs, Inc.

HarperDB

Hazelcast

Microsoft

Paradigma Software

Initial release

2016

2017

2008

2014

1999

Current release

3.1, August 2021

5.3.6, November 2023

5.7.5

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

free community edition available

Open Source

Apache Version 2; commercial licenses available

commercial

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

Node.js

Java

Server operating systems

Linux
OS X
Windows

Linux
OS X

All OS with a Java VM

hosted

Linux
OS X
Windows

Data scheme

schema-free

dynamic schema

schema-free

yes

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.

yes

the object must implement a serialization strategy

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like data manipulation statements

SQL-like query language

yes

APIs and other access methods

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

JCache
JPA
Memcached protocol
RESTful HTTP API

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

ODBC

Supported programming languages

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

.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#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

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

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

Custom Functions

since release 3.1

yes

Event Listeners, Executor Services

JavaScript

yes

Triggers

yes

Events

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

yes

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

Synchronous replication via Raft

yes

the nodes on which a table resides can be defined

yes

Replicated Map

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic execution of specific operations

one or two-phase-commit; repeatable reads; read commited

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

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

Planned for future releases

Access rights for users and roles

Role-based access control

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

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