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DBMS > Coveo vs. Google Cloud Bigtable vs. Manticore Search vs. Sphinx

System Properties Comparison Coveo vs. Google Cloud Bigtable vs. Manticore Search vs. Sphinx

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Editorial information provided by DB-Engines
NameCoveo  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonManticore Search  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionAI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code developmentGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Multi-storage database for search, including full-text search.Open source search engine for searching in data from different sources, e.g. relational databases
Primary database modelSearch engineKey-value store
Wide column store
Search engineSearch engine
Secondary database modelsTime Series DBMS infousing the Manticore Columnar Library
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.11
Rank#118  Overall
#11  Search engines
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score0.29
Rank#302  Overall
#21  Search engines
Score5.95
Rank#55  Overall
#5  Search engines
Websitewww.coveo.comcloud.google.com/­bigtablemanticoresearch.comsphinxsearch.com
Technical documentationdocs.coveo.comcloud.google.com/­bigtable/­docsmanual.manticoresearch.comsphinxsearch.com/­docs
DeveloperCoveoGoogleManticore SoftwareSphinx Technologies Inc.
Initial release2012201520172001
Current release6.0, February 20233.5.1, February 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoGPL version 2Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++
Server operating systemshostedhostedFreeBSD
Linux
macOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemehybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configurationschema-freeFixed schemayes
Typing infopredefined data types such as float or dateyesnoInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Booleanno
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.nonoCan index from XML
Secondary indexesyesnoyes infofull-text index on all search fieldsyes infofull-text index on all search fields
SQL infoSupport of SQLnonoSQL-like query languageSQL-like query language (SphinxQL)
APIs and other access methodsRESTful HTTP APIgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
Proprietary protocol
Supported programming languagesC#
Java
JavaScript
Python
C#
C++
Go
Java
JavaScript (Node.js)
Python
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnonouser defined functionsno
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodesyesShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyesInternal replication in Colossus, and regional replication between two clusters in different zonesSynchronous replication based on Galera librarynone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesAtomic single-row operationsyes infoisolated transactions for atomic changes and binary logging for safe writesno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Manticore index.yes 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.no
User concepts infoAccess controlgranular access controls, API key management, content filtersAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nono

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More resources
CoveoGoogle Cloud BigtableManticore SearchSphinx
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