DB-EnginesextremeDB - Data management wherever you need itEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by Redgate Software

DBMS > Amazon DocumentDB vs. Apache IoTDB vs. Hawkular Metrics vs. Qdrant

System Properties Comparison Amazon DocumentDB vs. Apache IoTDB vs. Hawkular Metrics vs. Qdrant

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonApache IoTDB  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonQdrant  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.A high-performance vector database with neural network or semantic-based matching
Primary database modelDocument storeTime Series DBMSTime Series DBMSVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#124  Overall
#22  Document stores
Score1.31
Rank#159  Overall
#14  Time Series DBMS
Score0.01
Rank#377  Overall
#39  Time Series DBMS
Score1.53
Rank#145  Overall
#7  Vector DBMS
Websiteaws.amazon.com/­documentdbiotdb.apache.orgwww.hawkular.orggithub.com/­qdrant/­qdrant
qdrant.tech
Technical documentationaws.amazon.com/­documentdb/­resourcesiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.hawkular.org/­hawkular-metrics/­docs/­user-guideqdrant.tech/­documentation
DeveloperApache Software FoundationCommunity supported by Red HatQdrant
Initial release2019201820142021
Current release1.1.0, April 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaRust
Server operating systemshostedAll OS with a Java VM (>= 1.8)Linux
OS X
Windows
Docker
Linux
macOS
Windows
Data schemeschema-freeyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyesNumbers, 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.nononono
Secondary indexesyesyesnoyes infoKeywords, numberic ranges, geo, full-text
SQL infoSupport of SQLnoSQL-like query languagenono
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBC
Native API
HTTP RESTgRPC
OpenAPI 3.0
RESTful HTTP/JSON API infoOpenAPI 3.0
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C
C#
C++
Go
Java
Python
Scala
Go
Java
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
Python
Rust
Server-side scripts infoStored proceduresnoyesno
Triggersnoyesyes infovia Hawkular Alerting
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding infobased on CassandraSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasselectable replication factor infobased on CassandraCollection-level replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)Integration with Hadoop and Sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Strong Consistency with Raft
Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual Consistency, tunable consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsnono
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.yesnoyes
User concepts infoAccess controlAccess rights for users and rolesyesnoKey-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
Amazon DocumentDBApache IoTDBHawkular MetricsQdrant
Recent citations in the news

Unlock the power of parallel indexing in Amazon DocumentDB
19 June 2024, AWS Blog

AWS announces Amazon DocumentDB zero-ETL integration with Amazon OpenSearch Service
16 May 2024, AWS Blog

Reduce cost and improve performance by migrating to Amazon DocumentDB 5.0
15 April 2024, AWS Blog

Update your Amazon DocumentDB TLS certificates: Expiring in 2024
28 March 2024, AWS Blog

Unlock the power of Amazon DocumentDB text search with real-world use cases
5 March 2024, AWS Blog

provided by Google News

AMD Zen 5 Not Affected By Inception/SRSO, mitigations=off Yields No Benefit On Ryzen 9000 Series
6 September 2024, Phoronix

TsFile: A Standard Format for IoT Time Series Data
27 February 2024, The New Stack

AMD EPYC 8534P / EPYC 8534PN Benchmarks - Siena Delivers Incredible Value & Energy Efficiency For Linux Servers Review
29 November 2023, Phoronix

Apache Promotes IoT Database Project
25 September 2020, Datanami

IoTDB Provides Data Management for Industrial Edge IT
15 October 2020, The New Stack

provided by Google News

Waiting for Red Hat OpenShift 4.0? Too late, 4.1 has already arrived…
5 June 2019, DevClass

provided by Google News

Qdrant review: A highly flexible option for vector search
29 July 2024, InfoWorld

Open source vector database startup Qdrant raises $28M
23 January 2024, TechCrunch

Vector database company Qdrant wants RAG to be more cost-effective
2 July 2024, VentureBeat

Qdrant Announces an Industry-First Hybrid Cloud Offering For Enterprise AI Applications
16 April 2024, businesswire.com

Qdrant unveils hybrid vector algorithm for improved RAG
2 July 2024, Blocks & Files

provided by Google News



Share this page

Featured Products

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

Neo4j logo

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

Milvus logo

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

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

SingleStore logo

The data platform to build your intelligent applications.
Try it free.

Present your product here