DBMS > Atos Standard Common Repository vs. Bangdb vs. Heroic vs. Microsoft Azure Table Storage vs. SwayDB

System Properties Comparison Atos Standard Common Repository vs. Bangdb vs. Heroic vs. Microsoft Azure Table Storage vs. SwayDB

Editorial information provided by DB-Engines
Name	Atos Standard Common Repository  Xexclude from comparison	Bangdb  Xexclude from comparison	Heroic  Xexclude from comparison	Microsoft Azure Table Storage  Xexclude from comparison	SwayDB  Xexclude from comparison
	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	Converged and high performance database for device data, events, time series, document and graph	Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch	A Wide Column Store for rapid development using massive semi-structured datasets	An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage
Primary database model	Document store Key-value store	Document store Graph DBMS Time Series DBMS	Time Series DBMS	Wide column store	Key-value store
Secondary database models		Spatial DBMS
DB-Engines Ranking measures the popularity of database management systems Trend Chart		Score 0.16 Rank #338   Overall #47   Document stores #32   Graph DBMS #31   Time Series DBMS	Score 0.46 Rank #265   Overall #22   Time Series DBMS	Score 4.04 Rank #77   Overall #6   Wide column stores	Score 0.04 Rank #387   Overall #61   Key-value stores
Website	atos.net/en/convergence-creators/portfolio/standard-common-repository	bangdb.com	github.com/­spotify/­heroic	azure.microsoft.com/­en-us/­services/­storage/­tables	swaydb.simer.au
Technical documentation		docs.bangdb.com	spotify.github.io/­heroic
Developer	Atos Convergence Creators	Sachin Sinha, BangDB	Spotify	Microsoft	Simer Plaha
Initial release	2016	2012	2014	2012	2018
Current release	1703	BangDB 2.0, October 2021
License Commercial or Open Source	commercial	Open Source BSD 3	Open Source Apache 2.0	commercial	Open Source GNU Affero GPL V3.0
Cloud-based only Only available as a cloud service	no	no	no	yes	no
DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed.
Implementation language	Java	C, C++	Java		Scala
Server operating systems	Linux	Linux		hosted
Data scheme	Schema and schema-less with LDAP views	schema-free	schema-free	schema-free	schema-free
Typing predefined data types such as float or date	optional	yes: string, long, double, int, geospatial, stream, events	yes	yes	no
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	no	no	no	no
Secondary indexes	yes	yes secondary, composite, nested, reverse, geospatial	yes via Elasticsearch	no	no
SQL Support of SQL	no	SQL like support with command line tool	no	no	no
APIs and other access methods	LDAP	Proprietary protocol RESTful HTTP API	HQL (Heroic Query Language, a JSON-based language) HTTP API	RESTful HTTP API
Supported programming languages	All languages with LDAP bindings	C C# C++ Java Python		.Net C# C++ Java JavaScript (Node.js) PHP Python Ruby	Java Kotlin Scala
Server-side scripts Stored procedures	no	no	no	no	no
Triggers	yes	yes, Notifications (with Streaming only)	no	no	no
Partitioning methods Methods for storing different data on different nodes	Sharding cell division	Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm	Sharding	Sharding Implicit feature of the cloud service	none
Replication methods Methods for redundantly storing data on multiple nodes	yes	selectable replication factor, Knob for CAP (enterprise version only)	yes	yes implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.	none
MapReduce Offers an API for user-defined Map/Reduce methods		no	no	no	no
Consistency concepts Methods to ensure consistency in a distributed system	Immediate Consistency or Eventual Consistency depending on configuration	Tunable consistency, set CAP knob accordingly	Eventual Consistency Immediate Consistency	Immediate Consistency	Immediate Consistency
Foreign keys Referential integrity	no	no	no	no	no
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data	Atomic execution of specific operations	ACID	no	optimistic locking	Atomic execution of operations
Concurrency Support for concurrent manipulation of data	yes	yes, optimistic concurrency control	yes	yes	yes
Durability Support for making data persistent	yes	yes, implements WAL (Write ahead log) as well	yes	yes	yes
In-memory capabilities Is there an option to define some or all structures to be held in-memory only.	yes	yes, run db with in-memory only mode	no	no	yes
User concepts Access control	LDAP bind authentication	yes (enterprise version only)		Access rights based on private key authentication or shared access signatures	no
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More resources
	Atos Standard Common Repository	Bangdb	Heroic	Microsoft Azure Table Storage	SwayDB
Recent citations in the news				Working with Azure to Use and Manage Data Lakes 7 March 2024, Simplilearn How to Use C# Azure.Data.Tables SDK with Azure Cosmos DB 9 July 2021, hackernoon.com How to use Azure Table storage in .Net 14 January 2019, InfoWorld How to write data to Azure Table Store with an Azure Function 14 April 2017, Experts Exchange Inside Azure File Storage 7 October 2015, Microsoft provided by Google News

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