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DBMS > Google Cloud Bigtable vs. OceanBase vs. Sadas Engine vs. Sphinx

System Properties Comparison Google Cloud Bigtable vs. OceanBase vs. Sadas Engine vs. Sphinx

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonOceanBase  Xexclude from comparisonSadas Engine  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, high available RDBMS compatible with Oracle and MySQLSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelKey-value store
Wide column store
Relational DBMSRelational DBMSSearch engine
Secondary database modelsDocument store
Wide column store
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
Score1.97
Rank#119  Overall
#58  Relational DBMS
Score0.00
Rank#385  Overall
#159  Relational DBMS
Score5.97
Rank#56  Overall
#5  Search engines
Websitecloud.google.com/­bigtableen.oceanbase.comwww.sadasengine.comsphinxsearch.com
Technical documentationcloud.google.com/­bigtable/­docsen.oceanbase.com/­docs/­oceanbase-databasewww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationsphinxsearch.com/­docs
DeveloperGoogleOceanBase infopreviously Alibaba and Ant GroupSADAS s.r.l.Sphinx Technologies Inc.
Initial release2015201020062001
Current release4.3.0, April 20248.03.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoCommercial license availablecommercial infofree trial version availableOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++C++
Server operating systemshostedLinuxAIX
Linux
Windows
FreeBSD
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.noyesno
Secondary indexesnoyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLnoyesyesSQL-like query language (SphinxQL)
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Proprietary native API
Table API
JDBC
ODBC
Proprietary protocol
Proprietary protocol
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
Ada infoin MySQL-compatible model
C infoin Oracle- and MySQL- compatible models
C++ infoin Oracle- and MySQL- compatible models
D infoin MySQL-compatible model
Delphi infoin MySQL-compatible model
Eiffel infoin MySQL-compatible model
Erlang infoin MySQL-compatible model
Haskell infoin MySQL-compatible model
Java infoin Oracle- and MySQL- compatible models
JavaScript (Node.js) infoin MySQL-compatible model
Objective-C infoin MySQL-compatible model
OCaml infoin MySQL-compatible model
Perl infoin MySQL-compatible model
PHP infoin MySQL-compatible model
Python infoin MySQL-compatible model
Ruby infoin MySQL-compatible model
Scheme infoin MySQL-compatible model
Tcl infoin MySQL-compatible model
.Net
C
C#
C++
Groovy
Java
PHP
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnoPL/SQL in oracle-compatible mode, MySQL Stored Procedure in mysql-compatible modenono
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by hash, key, range, range columns, list, and list columns)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 zonesMulti-source replication using Paxosnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
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 integritynoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes 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 infomanaged by 'Learn by Usage'
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and roles according to SQL-standardAccess rights for users, groups and roles according to SQL-standardno

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More resources
Google Cloud BigtableOceanBaseSadas EngineSphinx
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