DBMS > Apache Phoenix vs. Datomic vs. Microsoft Azure Cosmos DB vs. SAP Advantage Database Server

System Properties Comparison Apache Phoenix vs. Datomic vs. Microsoft Azure Cosmos DB vs. SAP Advantage Database Server

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Editorial information provided by DB-Engines

Name

SAP Advantage Database Server seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Globally distributed, horizontally scalable, multi-model database service

Low-cost RDBMS with access to ISAM and FoxPro data structures

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	2.06
Rank	#123	Overall
	#58	Relational DBMS

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

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

Website

phoenix.apache.org

www.datomic.com

azure.microsoft.com/services/cosmos-db

www.sap.com/products/advantage-database-server.html

Technical documentation

phoenix.apache.org

docs.datomic.com

learn.microsoft.com/azure/cosmos-db

Developer

Apache Software Foundation

Cognitect

Microsoft

Sybase, SAP

Initial release

2014

2012

2014

1993

Current release

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

1.0.7075, December 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

limited edition free

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

Java, Clojure

Server operating systems

Linux
Unix
Windows

All OS with a Java VM

hosted

Linux
Windows

Data scheme

yes

late-bound, schema-on-read capabilities

yes

schema-free

yes

Typing

predefined data types such as float or date

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

yes

SQL

Support of SQL

yes

SQL-like query language

yes

APIs and other access methods

JDBC

RESTful HTTP API

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

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

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

Clojure
Java

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

Delphi
Perl
PHP

Server-side scripts

Stored procedures

user defined functions

yes

Transaction Functions

JavaScript

yes

Triggers

By using transaction functions

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

But extensive use of caching in the application peers

Sharding

Implicit feature of the cloud service

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

But extensive use of caching in the application peers

yes

Implicit feature of the cloud service

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or 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

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

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

recommended only for testing and development

caching of (temporary) tables can be configured

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

fine grained access rights according to SQL-standard

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