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DBMS > Google Cloud Bigtable vs. IRONdb vs. Milvus vs. SiteWhere

System Properties Comparison Google Cloud Bigtable vs. IRONdb vs. Milvus vs. SiteWhere

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonIRONdb  Xexclude from comparisonMilvus  Xexclude from comparisonSiteWhere  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityA DBMS designed for efficient storage of vector data and vector similarity searchesM2M integration platform for persisting/querying time series data
Primary database modelKey-value store
Wide column store
Time Series DBMSVector DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score2.78
Rank#103  Overall
#3  Vector DBMS
Score0.06
Rank#383  Overall
#43  Time Series DBMS
Websitecloud.google.com/­bigtablewww.circonus.com/solutions/time-series-database/milvus.iogithub.com/­sitewhere/­sitewhere
Technical documentationcloud.google.com/­bigtable/­docsdocs.circonus.com/irondb/category/getting-startedmilvus.io/­docs/­overview.mdsitewhere1.sitewhere.io/­index.html
DeveloperGoogleCirconus LLC.SiteWhere
Initial release2015201720192010
Current releaseV0.10.20, January 20182.4.4, May 2024
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2.0Open Source infoCommon Public Attribution License Version 1.0
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.
Zilliz Cloud – Cloud-native service for Milvus
Implementation languageC and C++C++, GoJava
Server operating systemshostedLinuxLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux
OS X
Windows
Data schemeschema-freeschema-freepredefined scheme
Typing infopredefined data types such as float or datenoyes infotext, numeric, histogramsVector, Numeric and Stringyes
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 indexesnononono
SQL infoSupport of SQLnoSQL-like query language (Circonus Analytics Query Language: CAQL)nono
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HTTP APIRESTful HTTP APIHTTP REST
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnoyes, in Luano
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic, metric affinity per nodeShardingSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesconfigurable replication factor, datacenter awareselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate consistency per node, eventual consistency across nodesBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsnonono
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.nonoyesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noRole based access control and fine grained access rightsUsers with fine-grained authorization concept
More information provided by the system vendor
Google Cloud BigtableIRONdbMilvusSiteWhere
Specific characteristicsMilvus is an open-source and cloud-native vector database built for production-ready...
» more
Competitive advantagesHighly available, versatile, and robust with millisecond latency. Supports batch...
» more
Typical application scenariosRAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more
Key customersMilvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more
Market metricsAs of January 2024, 25k+ GitHub stars 10M+ downloads and installations​ ​ 3k+ enterprise...
» more
Licensing and pricing modelsMilvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
» more

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More resources
Google Cloud BigtableIRONdbMilvusSiteWhere
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