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DBMS > Google Cloud Bigtable vs. Kinetica vs. Microsoft Azure Data Explorer vs. Vertica

System Properties Comparison Google Cloud Bigtable vs. Kinetica vs. Microsoft Azure Data Explorer vs. Vertica

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Fully vectorized database across both GPUs and CPUsFully managed big data interactive analytics platformCloud 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 modelKey-value store
Wide column store
Relational DBMSRelational DBMS infocolumn orientedRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
Document 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
Score2.97
Rank#92  Overall
#15  Key-value stores
#8  Wide column stores
Score0.42
Rank#261  Overall
#120  Relational DBMS
Score3.28
Rank#83  Overall
#45  Relational DBMS
Score9.62
Rank#42  Overall
#26  Relational DBMS
Websitecloud.google.com/­bigtablewww.kinetica.comazure.microsoft.com/­services/­data-explorerwww.vertica.com
Technical documentationcloud.google.com/­bigtable/­docsdocs.kinetica.comdocs.microsoft.com/­en-us/­azure/­data-explorervertica.com/­documentation
DeveloperGoogleKineticaMicrosoftOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2015201220192005
Current release7.1, August 2021cloud service with continuous releases12.0.3, January 2023
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud serviceyesnoyesno 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 languageC, C++C++
Server operating systemshostedLinuxhostedLinux
Data schemeschema-freeyesFixed schema with schema-less datatypes (dynamic)Yes, 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 datenoyesyes 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 Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnoSQL-like DML and DDL statementsKusto Query Language (KQL), SQL subsetFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C++
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnouser defined functionsYes, possible languages: KQL, Python, Ryes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud servicehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replicationyes 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 methodsyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsnonoACID
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 infoGPU vRAM or System RAMnono
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and roles on table levelAzure Active Directory Authenticationfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

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More resources
Google Cloud BigtableKineticaMicrosoft Azure Data ExplorerVertica infoOpenText™ Vertica™
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