DB-EnginesExtremeDB for everyone with an RTOSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Hawkular Metrics vs. LMDB vs. MonetDB vs. Qdrant

System Properties Comparison Hawkular Metrics vs. LMDB vs. MonetDB vs. Qdrant

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameHawkular Metrics  Xexclude from comparisonLMDB  Xexclude from comparisonMonetDB  Xexclude from comparisonQdrant  Xexclude from comparison
DescriptionHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.A high performant, light-weight, embedded key-value database libraryA relational database management system that stores data in columnsA high-performance vector database with neural network or semantic-based matching
Primary database modelTime Series DBMSKey-value storeRelational DBMSVector DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.08
Rank#366  Overall
#39  Time Series DBMS
Score2.09
Rank#121  Overall
#20  Key-value stores
Score1.72
Rank#141  Overall
#64  Relational DBMS
Score1.28
Rank#167  Overall
#8  Vector DBMS
Websitewww.hawkular.orgwww.symas.com/­symas-embedded-database-lmdbwww.monetdb.orggithub.com/­qdrant/­qdrant
qdrant.tech
Technical documentationwww.hawkular.org/­hawkular-metrics/­docs/­user-guidewww.lmdb.tech/­docwww.monetdb.org/­Documentationqdrant.tech/­documentation
DeveloperCommunity supported by Red HatSymasMonetDB BVQdrant
Initial release2014201120042021
Current release0.9.32, January 2024Dec2023 (11.49), December 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0Open SourceOpen Source infoMozilla Public License 2.0Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaCCRust
Server operating systemsLinux
OS X
Windows
Linux
Unix
Windows
FreeBSD
Linux
OS X
Solaris
Windows
Docker
Linux
macOS
Windows
Data schemeschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesNumbers, Strings, Geo, Boolean
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nonono
Secondary indexesnonoyesyes infoKeywords, numberic ranges, geo, full-text
SQL infoSupport of SQLnonoyes infoSQL 2003 with some extensionsno
APIs and other access methodsHTTP RESTJDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
gRPC
OpenAPI 3.0
RESTful HTTP/JSON API infoOpenAPI 3.0
Supported programming languagesGo
Java
Python
Ruby
.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl
C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
.Net
Go
Java
JavaScript (Node.js)
Python
Rust
Server-side scripts infoStored proceduresnonoyes, in SQL, C, R
Triggersyes infovia Hawkular Alertingnoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandranoneSharding via remote tablesSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on Cassandranonenone infoSource-replica replication available in experimental statusCollection-level replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate ConsistencyEventual Consistency, tunable consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlnonofine grained access rights according to SQL-standardKey-based authentication

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Hawkular MetricsLMDBMonetDBQdrant
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

The Tom Brady Data Biography
8 September 2023, StatsBomb

Automating SAP S/4HANA Migration with IT-Conductor, BGP Managed Services, and AWS | Amazon Web Services
22 August 2023, AWS Blog

The Lightning Memory-mapped Database
2 March 2016, InfoQ.com

Akamai launches managed database service – Blocks and Files
25 April 2022, Blocks and Files

Jaxon Repp on HarperDB Distributed Database Platform
23 March 2022, InfoQ.com

provided by Google News

In 2024 the MonetDB Foundation was established for the preservation, maintenance and further development of the ...
31 January 2024, Centrum Wiskunde & Informatica (CWI)

MonetDB Secures Investment From (and Partners With) ServiceNow
9 December 2021, Datanami

PostgreSQL, MonetDB, and Too-Big-for-Memory Data in R - Part I - DataScienceCentral.com
6 April 2018, Data Science Central

How MonetDB Exploits Modern CPU Performance | by Dwi Prasetyo Adi Nugroho
14 January 2020, Towards Data Science

MonetDB Solutions secures investment from ServiceNow
30 September 2019, Centrum Wiskunde & Informatica (CWI)

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



Share this page

Featured Products

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Present your product here