DBMS > Atos Standard Common Repository vs. HarperDB vs. MaxDB vs. SAP HANA vs. SingleStore

System Properties Comparison Atos Standard Common Repository vs. HarperDB vs. MaxDB vs. SAP HANA vs. SingleStore

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

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

A robust and reliable RDBMS optimized to run all major SAP solutions

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

MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type

Primary database model

Document store
Key-value store

Document store

Relational DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

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

Score	0.55
Rank	#248	Overall
	#38	Document stores

Score	2.32
Rank	#112	Overall
	#55	Relational DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	5.60
Rank	#62	Overall
	#35	Relational DBMS

Website

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

www.harperdb.io

maxdb.sap.com

www.sap.com/products/hana.html

www.singlestore.com

Technical documentation

docs.harperdb.io/docs

maxdb.sap.com/documentation

help.sap.com/hana

docs.singlestore.com

Developer

Atos Convergence Creators

HarperDB

SAP, acquired from Software AG (Adabas-D) in 1997

SAP

SingleStore Inc.

Initial release

2016

2017

1984

2010

2013

Current release

1703

3.1, August 2021

7.9.10.12, February 2024

2.0 SPS07 (April 4, 2023), April 2023

8.5, January 2024

License

Commercial or Open Source

commercial

free community edition available

commercial

Limited community edition free

commercial

free developer edition available

Cloud-based only

Only available as a cloud service

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.

SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities

Implementation language

Java

Node.js

C++

C++, Go

Server operating systems

Linux

Linux
OS X

AIX
HP-UX
Linux
Solaris
Windows

Appliance or cloud-service

Linux

64 bit version required

Data scheme

Schema and schema-less with LDAP views

dynamic schema

yes

Typing

predefined data types such as float or date

optional

yes

JSON data 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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like data manipulation statements

yes

but no triggers and foreign keys

APIs and other access methods

LDAP

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

ADO.NET
JDBC
ODBC
WebDAV

JDBC
ODBC

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

Supported programming languages

All languages with LDAP bindings

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

.Net
C#
Java
Perl
PHP
Python

Bash
C
C#
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Custom Functions

since release 3.1

yes

SQLScript, R

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

A table resides as a whole on one (or more) nodes in a cluster

none

yes

Sharding

hash partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

the nodes on which a table resides can be defined

Source-replica replication

yes

Source-replica replication

stores two copies of each physical data partition on two separate nodes

MapReduce

Offers an API for user-defined Map/Reduce methods

can define user-defined aggregate functions for map-reduce-style calculations

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

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

yes, using LMDB

yes

All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via 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

LDAP bind authentication

Access rights for users and roles

fine grained access rights according to SQL-standard

yes

Fine grained access control via users, groups and roles

More information provided by the system vendor

Specific characteristics

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Key customers

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Market metrics

Customers in various industries worldwide including US and International Industry...
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Licensing and pricing models

F ree Tier and Enterprise Edition
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