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DBMS > Apache Impala vs. Google Cloud Firestore vs. Microsoft SQL Server vs. Prometheus

System Properties Comparison Apache Impala vs. Google Cloud Firestore vs. Microsoft SQL Server vs. Prometheus

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonMicrosoft SQL Server  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.Microsofts flagship relational DBMSOpen-source Time Series DBMS and monitoring system
Primary database modelRelational DBMSDocument storeRelational DBMSTime Series DBMS
Secondary database modelsDocument storeDocument store
Graph DBMS
Spatial DBMS
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
Score821.56
Rank#3  Overall
#3  Relational DBMS
Score7.69
Rank#50  Overall
#3  Time Series DBMS
Websiteimpala.apache.orgfirebase.google.com/­products/­firestorewww.microsoft.com/­en-us/­sql-serverprometheus.io
Technical documentationimpala.apache.org/­impala-docs.htmlfirebase.google.com/­docs/­firestorelearn.microsoft.com/­en-US/­sql/­sql-serverprometheus.io/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGoogleMicrosoft
Initial release2013201719892015
Current release4.1.0, June 2022SQL Server 2022, November 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercial inforestricted free version is availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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SQLServer Flex @ STACKIT offers a managed version of SQL Server with adjustable CPU, RAM, storage amount and speed, in enterprise grade to perfectly match all application requirements. All services are 100% GDPR-compliant.
Implementation languageC++C++Go
Server operating systemsLinuxhostedLinux
Windows
Linux
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesNumeric 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.nonoyesno infoImport of XML data possible
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyesno
APIs and other access methodsJDBC
ODBC
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBCGo
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic
.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 FunctionsTransact SQL, .NET languages, R, Python and (with SQL Server 2019) Javano
Triggersnoyes, with Cloud Functionsyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingtables can be distributed across several files (horizontal partitioning); sharding through federationSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replicationyes, but depending on the SQL-Server Editionyes infoby Federation
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceUsing Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistencynone
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesACIDno
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.noyesno
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.fine grained access rights according to SQL-standardno

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