DBMS > Microsoft Azure Table Storage vs. Pinecone vs. SAP HANA vs. UniData,UniVerse

System Properties Comparison Microsoft Azure Table Storage vs. Pinecone vs. SAP HANA vs. UniData,UniVerse

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Editorial information provided by DB-Engines

Name

Description

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

A managed, cloud-native vector database

In-memory, column based data store. Available as appliance or cloud service

MultiValue database and application server with SQL mapping layer and meta database capabilities

Primary database model

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	3.55
Rank	#80	Overall
	#6	Wide column stores

Score	3.02
Rank	#87	Overall
	#3	Vector DBMS

Score	41.32
Rank	#23	Overall
	#16	Relational DBMS

Score	2.25
Rank	#112	Overall
	#2	Multivalue DBMS

Website

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

www.pinecone.io

www.sap.com/products/hana.html

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-unidata

Technical documentation

docs.pinecone.io/docs/overview

help.sap.com/hana

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

Developer

Microsoft

Pinecone Systems, Inc

SAP

Rocket Software

Initial release

2012

2019

2010

1985

Current release

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Server operating systems

hosted

Appliance or cloud-service

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

String, Number, Boolean

yes

optional

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

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP API

JDBC
ODBC

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

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

Python

.Net
Basic

U2 Basic
C
Java

Server-side scripts

Stored procedures

SQLScript, R

yes

Triggers

yes

U2 Basic

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

optimistic locking

ACID

configurable

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 rights based on private key authentication or shared access signatures

yes

Access rights according to SQL-standard and operating system based

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