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DBMS > EXASOL vs. Google Cloud Firestore vs. Microsoft Azure Data Explorer vs. Splunk vs. Vertica

System Properties Comparison EXASOL vs. Google Cloud Firestore vs. Microsoft Azure Data Explorer vs. Splunk vs. Vertica

Editorial information provided by DB-Engines
NameEXASOL  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSplunk  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Cloud 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 platformAnalytics Platform for Big DataCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelRelational DBMSDocument storeRelational DBMS infocolumn orientedSearch engineRelational DBMS infoColumn oriented
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
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.99
Rank#124  Overall
#58  Relational DBMS
Score7.85
Rank#51  Overall
#8  Document stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score86.45
Rank#14  Overall
#2  Search engines
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitewww.exasol.comfirebase.google.com/­products/­firestoreazure.microsoft.com/­services/­data-explorerwww.splunk.comwww.vertica.com
Technical documentationwww.exasol.com/­resourcesfirebase.google.com/­docs/­firestoredocs.microsoft.com/­en-us/­azure/­data-explorerdocs.splunk.com/­Documentation/­Splunkvertica.com/­documentation
DeveloperExasolGoogleMicrosoftSplunk Inc.OpenText infopreviously Micro Focus and Hewlett Packard
Initial release20002017201920032005
Current releasecloud service with continuous releases12.0.3, January 2023
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercial infoLimited free edition and free developer edition availablecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenoyesyesnono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++
Server operating systemshostedhostedLinux
OS X
Solaris
Windows
Linux
Data schemeyesschema-freeFixed schema with schema-less datatypes (dynamic)yesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
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-typesyesyes
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.nonoyesyesno
Secondary indexesyesyesall fields are automatically indexedyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLyesnoKusto Query Language (KQL), SQL subsetno infoSplunk Search Processing Language for search commandsFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methods.Net
JDBC
ODBC
WebSocket
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP RESTADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesJava
Lua
Python
R
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C#
Java
JavaScript
PHP
Python
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresuser defined functionsyes, Firebase Rules & Cloud FunctionsYes, possible languages: KQL, Python, Ryesyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyesyes, with Cloud Functionsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceShardinghorizontal partitioning, hierarchical partitioning
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.Multi-source replicationMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoHadoop integrationUsing Cloud DataflowSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyesno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesnono infoA 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searchingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonono
User concepts infoAccess controlAccess rights for users, groups and roles according to SQL-standardAccess 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 AuthenticationAccess rights for users and rolesfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
EXASOLGoogle Cloud FirestoreMicrosoft Azure Data ExplorerSplunkVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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EXASOLGoogle Cloud FirestoreMicrosoft Azure Data ExplorerSplunkVertica infoOpenText™ Vertica™
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