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DBMS > Apache Impala vs. Firebase Realtime Database vs. Microsoft SQL Server vs. RavenDB

System Properties Comparison Apache Impala vs. Firebase Realtime Database vs. Microsoft SQL Server vs. RavenDB

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonMicrosoft SQL Server  Xexclude from comparisonRavenDB  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.Microsofts flagship relational DBMSOpen Source Operational and Transactional Enterprise NoSQL Document Database
Primary database modelRelational DBMSDocument storeRelational DBMSDocument store
Secondary database modelsDocument storeDocument store
Graph DBMS
Spatial DBMS
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score15.06
Rank#39  Overall
#24  Relational DBMS
Score15.07
Rank#38  Overall
#6  Document stores
Score845.81
Rank#3  Overall
#3  Relational DBMS
Score3.47
Rank#95  Overall
#16  Document stores
Websiteimpala.apache.orgfirebase.google.com/­products/­realtime-databasewww.microsoft.com/­en-us/­sql-serverravendb.net
Technical documentationimpala.apache.org/­impala-docs.htmlfirebase.google.com/­docs/­databaselearn.microsoft.com/­en-US/­sql/­sql-serverravendb.net/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGoogle infoacquired by Google 2014MicrosoftHibernating Rhinos
Initial release2013201219892010
Current release4.1.0, June 2022SQL Server 2022, November 20225.4, July 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercial inforestricted free version is availableOpen Source infoAGPL version 3, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++C#
Server operating systemsLinuxhostedLinux
Windows
Linux
macOS
Raspberry Pi
Windows
Data schemeyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesyesno
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.nonoyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyesSQL-like query language (RQL)
APIs and other access methodsJDBC
ODBC
Android
iOS
JavaScript API
RESTful HTTP API
ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCJava
JavaScript
Objective-C
C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducelimited functionality with using 'rules'Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Javayes
TriggersnoCallbacks are triggered when data changesyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingtables can be distributed across several files (horizontal partitioning); sharding through federationSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes, but depending on the SQL-Server EditionMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate ConsistencyDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesACIDACID, Cluster-wide transaction available
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.noyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosyes, based on authentication and database rulesfine grained access rights according to SQL-standardAuthorization levels configured per client per database

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Apache ImpalaFirebase Realtime DatabaseMicrosoft SQL ServerRavenDB
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