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DBMS > Google Cloud Bigtable vs. Microsoft Azure Table Storage vs. Sadas Engine vs. SiriDB vs. Sphinx

System Properties Comparison Google Cloud Bigtable vs. Microsoft Azure Table Storage vs. Sadas Engine vs. SiriDB vs. Sphinx

Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonSadas Engine  Xexclude from comparisonSiriDB  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 Wide Column Store for rapid development using massive semi-structured datasetsSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsOpen Source Time Series DBMSOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelKey-value store
Wide column store
Wide column storeRelational DBMSTime Series 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
Score4.48
Rank#75  Overall
#6  Wide column stores
Score0.00
Rank#383  Overall
#158  Relational DBMS
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websitecloud.google.com/­bigtableazure.microsoft.com/­en-us/­services/­storage/­tableswww.sadasengine.comsiridb.comsphinxsearch.com
Technical documentationcloud.google.com/­bigtable/­docswww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationdocs.siridb.comsphinxsearch.com/­docs
DeveloperGoogleMicrosoftSADAS s.r.l.CesbitSphinx Technologies Inc.
Initial release20152012200620172001
Current release8.03.5.1, February 2023
License infoCommercial or Open Sourcecommercialcommercialcommercial infofree trial version availableOpen Source infoMIT LicenseOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++CC++
Server operating systemshostedhostedAIX
Linux
Windows
LinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeschema-freeyesyesyes
Typing infopredefined data types such as float or datenoyesyesyes infoNumeric datano
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.nononono
Secondary indexesnonoyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLnonoyesnoSQL-like query language (SphinxQL)
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
RESTful HTTP APIJDBC
ODBC
Proprietary protocol
HTTP APIProprietary protocol
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C#
C++
Groovy
Java
PHP
Python
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnonononono
Triggersnonononono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud servicehorizontal partitioningShardingSharding 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 zonesyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.noneyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsoptimistic lockingnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes 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.nonoyes infomanaged by 'Learn by Usage'yes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights based on private key authentication or shared access signaturesAccess rights for users, groups and roles according to SQL-standardsimple rights management via user accountsno

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More resources
Google Cloud BigtableMicrosoft Azure Table StorageSadas EngineSiriDBSphinx
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