DBMS > Atos Standard Common Repository vs. LeanXcale vs. Pinecone vs. SAP HANA

System Properties Comparison Atos Standard Common Repository vs. LeanXcale vs. Pinecone vs. SAP HANA

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Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

A managed, cloud-native vector database

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

Primary database model

Document store
Key-value store

Key-value store
Relational DBMS

Vector DBMS

Relational DBMS

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	0.36
Rank	#280	Overall
	#40	Key-value stores
	#129	Relational DBMS

Score	3.23
Rank	#92	Overall
	#3	Vector DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

atos.net/en/convergence-creators/portfolio/standard-common-repository

www.leanxcale.com

www.pinecone.io

www.sap.com/products/hana.html

Technical documentation

docs.pinecone.io/docs/overview

help.sap.com/hana

Developer

Atos Convergence Creators

LeanXcale

Pinecone Systems, Inc

SAP

Initial release

2016

2015

2019

2010

Current release

1703

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

Java

Server operating systems

Linux

hosted

Appliance or cloud-service

Data scheme

Schema and schema-less with LDAP views

yes

Typing

predefined data types such as float or date

optional

String, Number, Boolean

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

Secondary indexes

yes

SQL

Support of SQL

yes

through Apache Derby

yes

APIs and other access methods

LDAP

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

RESTful HTTP API

JDBC
ODBC

Supported programming languages

All languages with LDAP bindings

C
Java
Scala

Python

Server-side scripts

Stored procedures

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of specific operations

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

LDAP bind authentication

yes

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