DBMS > Atos Standard Common Repository vs. Badger vs. Google Cloud Datastore vs. VelocityDB

System Properties Comparison Atos Standard Common Repository vs. Badger vs. Google Cloud Datastore vs. VelocityDB

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Editorial information provided by DB-Engines
Name	Atos Standard Common Repository  Xexclude from comparison	Badger  Xexclude from comparison	Google Cloud Datastore  Xexclude from comparison	VelocityDB  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	An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.	Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform	A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)
Primary database model	Document store Key-value store	Key-value store	Document store	Graph DBMS Object oriented DBMS
DB-Engines Ranking measures the popularity of database management systems Trend Chart		Score 0.22 Rank #320   Overall #47   Key-value stores	Score 4.36 Rank #72   Overall #12   Document stores	Score 0.11 Rank #354   Overall #37   Graph DBMS #15   Object oriented DBMS
Website	atos.net/en/convergence-creators/portfolio/standard-common-repository	github.com/­dgraph-io/­badger	cloud.google.com/­datastore	velocitydb.com
Technical documentation		godoc.org/­github.com/­dgraph-io/­badger	cloud.google.com/­datastore/­docs	velocitydb.com/­UserGuide
Developer	Atos Convergence Creators	DGraph Labs	Google	VelocityDB Inc
Initial release	2016	2017	2008	2011
Current release	1703			7.x
License Commercial or Open Source	commercial	Open Source Apache 2.0	commercial	commercial
Cloud-based only Only available as a cloud service	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	Go		C#
Server operating systems	Linux	BSD Linux OS X Solaris Windows	hosted	Any that supports .NET
Data scheme	Schema and schema-less with LDAP views	schema-free	schema-free	yes
Typing predefined data types such as float or date	optional	no	yes, details here	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	no	no	no
Secondary indexes	yes	no	yes	yes
SQL Support of SQL	no	no	SQL-like query language (GQL)	no
APIs and other access methods	LDAP		gRPC (using protocol buffers) API RESTful HTTP/JSON API	.Net
Supported programming languages	All languages with LDAP bindings	Go	.Net Go Java JavaScript (Node.js) PHP Python Ruby	.Net
Server-side scripts Stored procedures	no	no	using Google App Engine	no
Triggers	yes	no	Callbacks using the Google Apps Engine	Callbacks are triggered when data changes
Partitioning methods Methods for storing different data on different nodes	Sharding cell division	none	Sharding	Sharding
Replication methods Methods for redundantly storing data on multiple nodes	yes	none	Multi-source replication using Paxos
MapReduce Offers an API for user-defined Map/Reduce methods		no	yes using Google Cloud Dataflow	no
Consistency concepts Methods to ensure consistency in a distributed system	Immediate Consistency or Eventual Consistency depending on configuration	none	Immediate Consistency or Eventual Consistency depending on type of query and configuration Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.	Immediate Consistency
Foreign keys Referential integrity	no	no	yes via ReferenceProperties or Ancestor paths	no
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data	Atomic execution of specific operations	no	ACID Serializable Isolation within Transactions, Read Committed outside of Transactions	ACID
Concurrency Support for concurrent manipulation of data	yes	yes	yes	yes
Durability Support for making data persistent	yes	yes	yes	yes
In-memory capabilities Is there an option to define some or all structures to be held in-memory only.	yes	no	no	yes
User concepts Access control	LDAP bind authentication	no	Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)	Based on Windows Authentication
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More resources
	Atos Standard Common Repository	Badger	Google Cloud Datastore	VelocityDB
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