DBMS > Apache Phoenix vs. Microsoft Azure Cosmos DB vs. Netezza vs. SiriDB vs. SpaceTime

System Properties Comparison Apache Phoenix vs. Microsoft Azure Cosmos DB vs. Netezza vs. SiriDB vs. SpaceTime

Editorial information provided by DB-Engines

Name

Description

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

Globally distributed, horizontally scalable, multi-model database service

Data warehouse and analytics appliance part of IBM PureSystems

Open Source Time Series DBMS

SpaceTime is a spatio-temporal DBMS with a focus on performance.

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Time Series DBMS

Spatial DBMS

Secondary database models

Spatial DBMS

Relational DBMS

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

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

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

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Website

phoenix.apache.org

azure.microsoft.com/services/cosmos-db

www.ibm.com/products/netezza

siridb.com

www.mireo.com/spacetime

Technical documentation

phoenix.apache.org

learn.microsoft.com/azure/cosmos-db

docs.siridb.com

Developer

Apache Software Foundation

Microsoft

IBM

Cesbit

Mireo

Initial release

2014

2000

2017

2020

Current release

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

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

MIT License

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

C++

Server operating systems

Linux
Unix
Windows

hosted

Linux

included in appliance

Linux

Data scheme

yes

late-bound, schema-on-read capabilities

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

yes

Numeric data

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

yes

SQL

Support of SQL

yes

SQL-like query language

yes

A subset of ANSI SQL is implemented

APIs and other access methods

JDBC

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

JDBC
ODBC
OLE DB

HTTP API

RESTful HTTP API

Supported programming languages

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

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

C
C++
Fortran
Java
Lua
Perl
Python
R

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

C#
C++
Python

Server-side scripts

Stored procedures

user defined functions

JavaScript

yes

Triggers

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Fixed-grid hypercubes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

Implicit feature of the cloud service

Source-replica replication

yes

Real-time block device replication (DRBD)

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

Access rights can be defined down to the item level

Users with fine-grained authorization concept

simple rights management via user accounts

yes

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