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DBMS > Google Cloud Bigtable vs. Lovefield vs. Microsoft Azure Data Explorer vs. Microsoft Azure Synapse Analytics vs. TimescaleDB

System Properties Comparison Google Cloud Bigtable vs. Lovefield vs. Microsoft Azure Data Explorer vs. Microsoft Azure Synapse Analytics vs. TimescaleDB

Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonLovefield  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonTimescaleDB  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.Embeddable relational database for web apps written in pure JavaScriptFully managed big data interactive analytics platformElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelKey-value store
Wide column store
Relational DBMSRelational DBMS infocolumn orientedRelational DBMSTime Series 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
Relational 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
Score0.22
Rank#306  Overall
#138  Relational DBMS
Score3.28
Rank#83  Overall
#45  Relational DBMS
Score18.98
Rank#31  Overall
#19  Relational DBMS
Score4.06
Rank#73  Overall
#5  Time Series DBMS
Websitecloud.google.com/­bigtablegoogle.github.io/­lovefieldazure.microsoft.com/­services/­data-explorerazure.microsoft.com/­services/­synapse-analyticswww.timescale.com
Technical documentationcloud.google.com/­bigtable/­docsgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mddocs.microsoft.com/­en-us/­azure/­data-explorerdocs.microsoft.com/­azure/­synapse-analyticsdocs.timescale.com
DeveloperGoogleGoogleMicrosoftMicrosoftTimescale
Initial release20152014201920162017
Current release2.1.12, February 2017cloud service with continuous releases2.15.0, May 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaScriptC++C
Server operating systemshostedserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafarihostedhostedLinux
OS X
Windows
Data schemeschema-freeyesFixed schema with schema-less datatypes (dynamic)yesyes
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-typesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.nonoyesnoyes
Secondary indexesnoyesall fields are automatically indexedyesyes
SQL infoSupport of SQLnoSQL-like query language infovia JavaScript builder patternKusto Query Language (KQL), SQL subsetyesyes infofull PostgreSQL SQL syntax
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
JavaScript.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C#
Java
PHP
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnonoYes, possible languages: KQL, Python, RTransact SQLuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
TriggersnoUsing read-only observersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infoImplicit feature of the cloud serviceSharding, horizontal partitioningyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesnoneyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yesSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infousing MemoryDBnono
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noAzure Active Directory Authenticationyesfine grained access rights according to SQL-standard

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More resources
Google Cloud BigtableLovefieldMicrosoft Azure Data ExplorerMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseTimescaleDB
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