DBMS > Atos Standard Common Repository vs. Hawkular Metrics vs. Lovefield vs. Qdrant

System Properties Comparison Atos Standard Common Repository vs. Hawkular Metrics vs. Lovefield vs. Qdrant

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Editorial information provided by DB-Engines
Name	Atos Standard Common Repository  Xexclude from comparison	Hawkular Metrics  Xexclude from comparison	Lovefield  Xexclude from comparison	Qdrant  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	Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.	Embeddable relational database for web apps written in pure JavaScript	A high-performance vector database with neural network or semantic-based matching
Primary database model	Document store Key-value store	Time Series DBMS	Relational DBMS	Vector DBMS
DB-Engines Ranking measures the popularity of database management systems Trend Chart		Score 0.08 Rank #366   Overall #39   Time Series DBMS	Score 0.33 Rank #286   Overall #131   Relational DBMS	Score 1.28 Rank #167   Overall #8   Vector DBMS
Website	atos.net/en/convergence-creators/portfolio/standard-common-repository	www.hawkular.org	google.github.io/­lovefield	github.com/­qdrant/­qdrant qdrant.tech
Technical documentation		www.hawkular.org/­hawkular-metrics/­docs/­user-guide	github.com/­google/­lovefield/­blob/­master/­docs/­spec_index.md	qdrant.tech/­documentation
Developer	Atos Convergence Creators	Community supported by Red Hat	Google	Qdrant
Initial release	2016	2014	2014	2021
Current release	1703		2.1.12, February 2017
License Commercial or Open Source	commercial	Open Source Apache 2.0	Open Source Apache 2.0	Open Source Apache Version 2.0
Cloud-based only Only available as a cloud service	no	no	no	no
DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed.
Implementation language	Java	Java	JavaScript	Rust
Server operating systems	Linux	Linux OS X Windows	server-less, requires a JavaScript environment (browser, Node.js) tested with Chrome, Firefox, IE, Safari	Docker Linux macOS Windows
Data scheme	Schema and schema-less with LDAP views	schema-free	yes	schema-free
Typing predefined data types such as float or date	optional	yes	yes	Numbers, Strings, Geo, Boolean
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 Keywords, numberic ranges, geo, full-text
SQL Support of SQL	no	no	SQL-like query language via JavaScript builder pattern	no
APIs and other access methods	LDAP	HTTP REST		gRPC OpenAPI 3.0 RESTful HTTP/JSON API OpenAPI 3.0
Supported programming languages	All languages with LDAP bindings	Go Java Python Ruby	JavaScript	.Net Go Java JavaScript (Node.js) Python Rust
Server-side scripts Stored procedures	no	no	no
Triggers	yes	yes via Hawkular Alerting	Using read-only observers
Partitioning methods Methods for storing different data on different nodes	Sharding cell division	Sharding based on Cassandra	none	Sharding
Replication methods Methods for redundantly storing data on multiple nodes	yes	selectable replication factor based on Cassandra	none	Collection-level replication
MapReduce Offers an API for user-defined Map/Reduce methods		no	no	no
Consistency concepts Methods to ensure consistency in a distributed system	Immediate Consistency or Eventual Consistency depending on configuration	Eventual Consistency based on Cassandra Immediate Consistency based on Cassandra		Eventual Consistency, tunable consistency
Foreign keys Referential integrity	no	no	yes
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data	Atomic execution of specific operations	no	ACID
Concurrency Support for concurrent manipulation of data	yes	yes	yes	yes
Durability Support for making data persistent	yes	yes	yes, by using IndexedDB or the cloud service Firebase Realtime Database	yes
In-memory capabilities Is there an option to define some or all structures to be held in-memory only.	yes	no	yes using MemoryDB	yes
User concepts Access control	LDAP bind authentication	no	no	Key-based authentication
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More resources
	Atos Standard Common Repository	Hawkular Metrics	Lovefield	Qdrant
Recent citations in the news		Waiting for Red Hat OpenShift 4.0? Too late, 4.1 has already arrived… • DEVCLASS 5 June 2019, DevClass provided by Google News		Open source vector database startup Qdrant raises $28M 23 January 2024, TechCrunch Qdrant Raises $28M to Advance Massive-Scale AI Applications 23 January 2024, businesswire.com Qdrant Hybrid Cloud is Now Available for OCI Customers: Managed Vector Search Engine for Data-Sensitive AI ... 16 April 2024, blogs.oracle.com Qdrant offers managed vector database for hybrid clouds 16 April 2024, InfoWorld Why Vector Data Services For AI Are A Moveable Feast 17 April 2024, Forbes provided by Google News

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