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DBMS > atoti vs. Google Cloud Bigtable vs. HugeGraph vs. Microsoft Azure AI Search vs. Sphinx

System Properties Comparison atoti vs. Google Cloud Bigtable vs. HugeGraph vs. Microsoft Azure AI Search vs. Sphinx

Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHugeGraph  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A fast-speed and highly-scalable Graph DBMSSearch-as-a-service for web and mobile app developmentOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelObject oriented DBMSKey-value store
Wide column store
Graph DBMSSearch engineSearch engine
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.56
Rank#245  Overall
#10  Object oriented DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score5.59
Rank#63  Overall
#7  Search engines
Score5.98
Rank#56  Overall
#5  Search engines
Websiteatoti.iocloud.google.com/­bigtablegithub.com/­hugegraph
hugegraph.apache.org
azure.microsoft.com/­en-us/­services/­searchsphinxsearch.com
Technical documentationdocs.atoti.iocloud.google.com/­bigtable/­docshugegraph.apache.org/­docslearn.microsoft.com/­en-us/­azure/­searchsphinxsearch.com/­docs
DeveloperActiveViamGoogleBaiduMicrosoftSphinx Technologies Inc.
Initial release2015201820152001
Current release0.9V13.5.1, February 2023
License infoCommercial or Open Sourcecommercial infofree versions availablecommercialOpen Source infoApache Version 2.0commercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenoyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaC++
Server operating systemshostedLinux
macOS
Unix
hostedFreeBSD
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 indexesnoyes infoalso supports composite index and range indexyesyes infofull-text index on all search fields
SQL infoSupport of SQLMultidimensional Expressions (MDX)nononoSQL-like query language (SphinxQL)
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Java API
RESTful HTTP API
TinkerPop Gremlin
RESTful HTTP APIProprietary protocol
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
Groovy
Java
Python
C#
Java
JavaScript
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresPythonnoasynchronous Gremlin script jobsnono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningShardingyes infodepending on used storage backend, e.g. Cassandra and HBaseSharding infoImplicit feature of the cloud serviceSharding 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 infodepending on used storage backend, e.g. Cassandra and HBaseyes infoImplicit feature of the cloud servicenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesvia hugegraph-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 ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infoedges in graphnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACIDnono
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyesyes
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.yesnoyesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users, roles and permissionsyes infousing Azure authenticationno

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More resources
atotiGoogle Cloud BigtableHugeGraphMicrosoft Azure AI SearchSphinx
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