DBMS > Apache Phoenix vs. Microsoft Azure SQL Database vs. NSDb vs. ObjectBox vs. OrigoDB

System Properties Comparison Apache Phoenix vs. Microsoft Azure SQL Database vs. NSDb vs. ObjectBox vs. OrigoDB

Editorial information provided by DB-Engines

Name

Description

A scale-out RDBMS with evolutionary schema built on Apache HBase

Database as a Service offering with high compatibility to Microsoft SQL Server

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Extremely fast embedded database for small devices, IoT and Mobile

A fully ACID in-memory object graph database

Primary database model

Relational DBMS

Time Series DBMS

Object oriented DBMS

Document store
Object oriented DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Time Series DBMS

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

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	77.99
Rank	#16	Overall
	#11	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	1.20
Rank	#170	Overall
	#5	Object oriented DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Website

phoenix.apache.org

azure.microsoft.com/en-us/products/azure-sql/database

nsdb.io

objectbox.io

origodb.com

Technical documentation

phoenix.apache.org

docs.microsoft.com/en-us/azure/azure-sql

nsdb.io/Architecture

docs.objectbox.io

origodb.com/docs

Developer

Apache Software Foundation

Microsoft

ObjectBox Limited

Robert Friberg et al

Initial release

2014

2010

2017

2009

under the name LiveDB

Current release

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

V12

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache Version 2.0

Open Source

Apache License 2.0

Open Source

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

C++

Java, Scala

C and C++

Server operating systems

Linux
Unix
Windows

hosted

Linux
macOS

Android
iOS
Linux
macOS
Windows

Linux
Windows

Data scheme

yes

late-bound, schema-on-read capabilities

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

yes

User defined using .NET types and collections

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

can be achieved using .NET

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

JDBC

ADO.NET
JDBC
ODBC

gRPC
HTTP REST
WebSocket

Proprietary native API

.NET Client API
HTTP API
LINQ

Supported programming languages

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

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

Java
Scala

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

.Net

Server-side scripts

Stored procedures

user defined functions

Transact SQL

yes

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes, with always 3 replicas available

online/offline synchronization between client and server

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

depending on model

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

yes

Write ahead log

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 Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

fine grained access rights according to SQL-standard

yes

Role based authorization

More information provided by the system vendor

News

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23 May 2024

On-device Vector Database for Dart/Flutter
21 May 2024

The first On-Device Vector Database: ObjectBox 4.0
16 May 2024

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7 May 2024

Edge AI: The era of on-device AI
23 April 2024

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Recent citations in the news

Supercharge SQL on Your Data in Apache HBase with Apache Phoenix | Amazon Web Services
2 June 2016, AWS Blog

Azure #HDInsight Apache Phoenix now supports Zeppelin
16 August 2018, azure.microsoft.com

Bridge the SQL-NoSQL gap with Apache Phoenix
4 February 2016, InfoWorld

Apache Calcite, FreeMarker, Gora, Phoenix, and Solr updated
27 March 2017, SDTimes.com

Hortonworks Starts Hadoop Summit with Data Platform Update -- ADTmag
28 June 2016, ADT Magazine

provided by Google News

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21 May 2024, azure.microsoft.com

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27 March 2024, InfoQ.com

Microsoft unveils Copilot for Azure SQL Database
27 March 2024, InfoWorld

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11 January 2024, Oracle

Microsoft Build 2024: Cosmos DB for NoSQL gets vector search
21 May 2024, InfoWorld

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21 June 2019, 1E9

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