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DBMS > Apache Impala vs. Google Cloud Firestore vs. Milvus vs. PouchDB vs. Prometheus

System Properties Comparison Apache Impala vs. Google Cloud Firestore vs. Milvus vs. PouchDB vs. Prometheus

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonMilvus  Xexclude from comparisonPouchDB  Xexclude from comparisonPrometheus  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopCloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.A DBMS designed for efficient storage of vector data and vector similarity searchesJavaScript DBMS with an API inspired by CouchDBOpen-source Time Series DBMS and monitoring system
Primary database modelRelational DBMSDocument storeVector DBMSDocument storeTime Series DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score7.36
Rank#53  Overall
#9  Document stores
Score2.78
Rank#103  Overall
#3  Vector DBMS
Score2.34
Rank#112  Overall
#21  Document stores
Score7.69
Rank#50  Overall
#3  Time Series DBMS
Websiteimpala.apache.orgfirebase.google.com/­products/­firestoremilvus.iopouchdb.comprometheus.io
Technical documentationimpala.apache.org/­impala-docs.htmlfirebase.google.com/­docs/­firestoremilvus.io/­docs/­overview.mdpouchdb.com/­guidesprometheus.io/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGoogleApache Software Foundation
Initial release20132017201920122015
Current release4.1.0, June 20222.4.4, May 20247.1.1, June 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoApache Version 2.0Open SourceOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Zilliz Cloud – Cloud-native service for Milvus
Implementation languageC++C++, GoJavaScriptGo
Server operating systemsLinuxhostedLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
server-less, requires a JavaScript environment (browser, Node.js)Linux
Windows
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesVector, Numeric and StringnoNumeric data only
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.nonononono infoImport of XML data possible
Secondary indexesyesyesnoyes infovia viewsno
SQL infoSupport of SQLSQL-like DML and DDL statementsnononono
APIs and other access methodsJDBC
ODBC
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
RESTful HTTP APIHTTP REST infoonly for PouchDB Server
JavaScript API
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBCGo
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C++
Go
Java
JavaScript (Node.js)
Python
JavaScript.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes, Firebase Rules & Cloud FunctionsnoView functions in JavaScriptno
Triggersnoyes, with Cloud Functionsnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infowith a proxy-based framework, named couchdb-loungeSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replicationMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
yes infoby Federation
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceUsing Cloud Dataflownoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Eventual Consistencynone
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backendyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.Role based access control and fine grained access rightsnono
More information provided by the system vendor
Apache ImpalaGoogle Cloud FirestoreMilvusPouchDBPrometheus
Specific characteristicsMilvus is an open-source and cloud-native vector database built for production-ready...
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Competitive advantagesHighly available, versatile, and robust with millisecond latency. Supports batch...
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Typical application scenariosRAG: retrieval augmented generation Video media : video understanding, video deduplication....
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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...
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More resources
Apache ImpalaGoogle Cloud FirestoreMilvusPouchDBPrometheus
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