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DBMS > FoundationDB vs. Google Cloud Spanner vs. Microsoft Azure Data Explorer vs. Postgres-XL vs. Vertica

System Properties Comparison FoundationDB vs. Google Cloud Spanner vs. Microsoft Azure Data Explorer vs. Postgres-XL vs. Vertica

Editorial information provided by DB-Engines
NameFoundationDB  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonPostgres-XL  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.
DescriptionOrdered key-value store. Core features are complimented by layers.A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.Fully managed big data interactive analytics platformBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresCloud 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 modelDocument store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Relational DBMSRelational DBMS infocolumn orientedRelational DBMSRelational 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
Document store
Spatial DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.06
Rank#185  Overall
#31  Document stores
#28  Key-value stores
#85  Relational DBMS
Score2.84
Rank#100  Overall
#51  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.53
Rank#254  Overall
#117  Relational DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitegithub.com/­apple/­foundationdbcloud.google.com/­spannerazure.microsoft.com/­services/­data-explorerwww.postgres-xl.orgwww.vertica.com
Technical documentationapple.github.io/­foundationdbcloud.google.com/­spanner/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerwww.postgres-xl.org/­documentationvertica.com/­documentation
DeveloperFoundationDBGoogleMicrosoftOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2013201720192014 infosince 2012, originally named StormDB2005
Current release6.2.28, November 2020cloud service with continuous releases10 R1, October 201812.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialOpen Source infoMozilla public licensecommercial 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++CC++
Server operating systemsLinux
OS X
Windows
hostedhostedLinux
macOS
Linux
Data schemeschema-free infosome layers support schemasyesFixed 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 dateno infosome layers support typingyesyes 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.noyesyes infoXML type, but no XML query functionalityno
Secondary indexesnoyesall fields are automatically indexedyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLsupported in specific SQL layer onlyyes infoQuery statements complying to ANSI 2011Kusto Query Language (KQL), SQL subsetyes infodistributed, parallel query executionFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsgRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languages.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
Go
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresin SQL-layer onlynoYes, possible languages: KQL, Python, Ruser defined functionsyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnonoyes 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 servicehorizontal partitioninghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication with 3 replicas for regional instances.yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-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 methodsnoyes infousing Google Cloud DataflowSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemLinearizable consistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityin SQL-layer onlyyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integritynoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoStrict serializable isolationnoACID infoMVCCACID
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.nononono
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Azure Active Directory Authenticationfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
FoundationDBGoogle Cloud SpannerMicrosoft Azure Data ExplorerPostgres-XLVertica 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...
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Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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More resources
FoundationDBGoogle Cloud SpannerMicrosoft Azure Data ExplorerPostgres-XLVertica infoOpenText™ Vertica™
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