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DBMS > Apache Drill vs. Google Cloud Firestore vs. Microsoft Azure Data Explorer vs. Spark SQL

System Properties Comparison Apache Drill vs. Google Cloud Firestore vs. Microsoft Azure Data Explorer vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache Drill  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionSchema-free SQL Query Engine for Hadoop, NoSQL and Cloud StorageCloud 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.Fully managed big data interactive analytics platformSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Relational DBMS
Document storeRelational DBMS infocolumn orientedRelational DBMS
Secondary database modelsDocument store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.95
Rank#127  Overall
#23  Document stores
#60  Relational DBMS
Score7.85
Rank#51  Overall
#8  Document stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitedrill.apache.orgfirebase.google.com/­products/­firestoreazure.microsoft.com/­services/­data-explorerspark.apache.org/­sql
Technical documentationdrill.apache.org/­docsfirebase.google.com/­docs/­firestoredocs.microsoft.com/­en-us/­azure/­data-explorerspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationGoogleMicrosoftApache Software Foundation
Initial release2012201720192014
Current release1.20.3, January 2023cloud service with continuous releases3.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScala
Server operating systemsLinux
OS X
Windows
hostedhostedLinux
OS X
Windows
Data schemeschema-freeschema-freeFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes
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
Secondary indexesnoyesall fields are automatically indexedno
SQL infoSupport of SQLSQL SELECT statement is SQL:2003 compliantnoKusto Query Language (KQL), SQL subsetSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
Supported programming languagesC++Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsyes, Firebase Rules & Cloud FunctionsYes, possible languages: KQL, Python, Rno
Triggersnoyes, with Cloud Functionsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesUsing Cloud DataflowSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentDepending on the underlying data sourceyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.Depending on the underlying data sourcenono
User concepts infoAccess controlDepending on the underlying data sourceAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.Azure Active Directory Authenticationno

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More resources
Apache DrillGoogle Cloud FirestoreMicrosoft Azure Data ExplorerSpark SQL
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