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DBMS > Google Cloud Bigtable vs. Graph Engine vs. Microsoft Azure Synapse Analytics vs. Sphinx

System Properties Comparison Google Cloud Bigtable vs. Graph Engine vs. Microsoft Azure Synapse Analytics vs. Sphinx

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonSphinx  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.A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelKey-value store
Wide column store
Graph DBMS
Key-value store
Relational DBMSSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websitecloud.google.com/­bigtablewww.graphengine.ioazure.microsoft.com/­services/­synapse-analyticssphinxsearch.com
Technical documentationcloud.google.com/­bigtable/­docswww.graphengine.io/­docs/­manualdocs.microsoft.com/­azure/­synapse-analyticssphinxsearch.com/­docs
DeveloperGoogleMicrosoftMicrosoftSphinx Technologies Inc.
Initial release2015201020162001
Current release3.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoMIT LicensecommercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation language.NET and CC++C++
Server operating systemshosted.NEThostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or datenoyesyesno
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.nonono
Secondary indexesnoyesyes infofull-text index on all search fields
SQL infoSupport of SQLnonoyesSQL-like query language (SphinxQL)
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
RESTful HTTP APIADO.NET
JDBC
ODBC
Proprietary protocol
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C#
C++
F#
Visual Basic
C#
Java
PHP
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnoyesTransact SQLno
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningSharding, horizontal partitioningSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
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
Foreign keys infoReferential integritynonono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yesno

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More resources
Google Cloud BigtableGraph Engine infoformer name: TrinityMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSphinx
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