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DBMS > Google Cloud Spanner vs. Microsoft Azure Data Explorer vs. Riak KV vs. STSdb vs. Vertica

System Properties Comparison Google Cloud Spanner vs. Microsoft Azure Data Explorer vs. Riak KV vs. STSdb vs. Vertica

Editorial information provided by DB-Engines
NameGoogle Cloud Spanner  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRiak KV  Xexclude from comparisonSTSdb  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionA 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 platformDistributed, fault tolerant key-value storeKey-Value Store with special method for indexing infooptimized for high performance using a special indexing methodCloud 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 DBMSRelational DBMS infocolumn orientedKey-value store infowith links between data sets and object tags for the creation of secondary indexesKey-value storeRelational 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
Score2.84
Rank#100  Overall
#51  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score4.01
Rank#79  Overall
#9  Key-value stores
Score0.10
Rank#357  Overall
#51  Key-value stores
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitecloud.google.com/­spannerazure.microsoft.com/­services/­data-explorergithub.com/­STSSoft/­STSdb4www.vertica.com
Technical documentationcloud.google.com/­spanner/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerwww.tiot.jp/­riak-docs/­riak/­kv/­latestvertica.com/­documentation
DeveloperGoogleMicrosoftOpenSource, formerly Basho TechnologiesSTS Soft SCOpenText infopreviously Micro Focus and Hewlett Packard
Initial release20172019200920112005
Current releasecloud service with continuous releases3.2.0, December 20224.0.8, September 201512.0.3, January 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache version 2, commercial enterprise editionOpen Source infoGPLv2, commercial license availablecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud serviceyesyesnonono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageErlangC#C++
Server operating systemshostedhostedLinux
OS X
WindowsLinux
Data schemeyesFixed schema with schema-less datatypes (dynamic)schema-freeyesYes, 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 dateyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesnoyes infoprimitive types and user defined types (classes)yes
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.noyesnono
Secondary indexesyesall fields are automatically indexedrestrictednoNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLyes infoQuery statements complying to ANSI 2011Kusto Query Language (KQL), SQL subsetnonoFull 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
HTTP API
Native Erlang Interface
.NET Client APIADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
C#
Java
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnoYes, possible languages: KQL, Python, RErlangnoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infopre-commit hooks and post-commit hooksnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceSharding infono "single point of failure"nonehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication with 3 replicas for regional instances.yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factornoneMulti-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 infousing Google Cloud DataflowSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyesnono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integritynono infolinks between data sets can be storednoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoStrict serializable isolationnononoACID
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.nonono
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Azure Active Directory Authenticationyes, using Riak Securitynofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Google Cloud SpannerMicrosoft Azure Data ExplorerRiak KVSTSdbVertica 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,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
» more

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More resources
Google Cloud SpannerMicrosoft Azure Data ExplorerRiak KVSTSdbVertica infoOpenText™ Vertica™
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