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DBMS > Amazon Neptune vs. GigaSpaces vs. Google Cloud Bigtable vs. mSQL vs. Sphinx

System Properties Comparison Amazon Neptune vs. GigaSpaces vs. Google Cloud Bigtable vs. mSQL vs. Sphinx

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonGigaSpaces  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonmSQL infoMini SQL  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.mSQL (Mini SQL) is a simple and lightweight RDBMSOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelGraph DBMS
RDF store
Document store
Object oriented DBMS infoValues are user defined objects
Key-value store
Wide column store
Relational DBMSSearch engine
Secondary database modelsGraph DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.20
Rank#119  Overall
#9  Graph DBMS
#5  RDF stores
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score1.27
Rank#167  Overall
#77  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websiteaws.amazon.com/­neptunewww.gigaspaces.comcloud.google.com/­bigtablehughestech.com.au/­products/­msqlsphinxsearch.com
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.gigaspaces.com/­latest/­landing.htmlcloud.google.com/­bigtable/­docssphinxsearch.com/­docs
DeveloperAmazonGigaspaces TechnologiesGoogleHughes TechnologiesSphinx Technologies Inc.
Initial release20172000201519942001
Current release15.5, September 20204.4, October 20213.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; Commercial licenses availablecommercialcommercial infofree licenses can be providedOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, C++, .NetCC++
Server operating systemshostedLinux
macOS
Solaris
Windows
hostedAIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesnoyesno
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.nono infoXML can be used for describing objects metadatanono
Secondary indexesnoyesnoyesyes infofull-text index on all search fields
SQL infoSupport of SQLnoSQL-99 for query and DML statementsnoA subset of ANSI SQL is implemented infono subqueries, aggregate functions, views, foreign keys, triggersSQL-like query language (SphinxQL)
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Proprietary protocol
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
.Net
C++
Java
Python
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
C
C++
Delphi
Java
Perl
PHP
Tcl
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnoyesnonono
Triggersnoyes, event driven architecturenonono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingnoneSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.Multi-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Internal replication in Colossus, and regional replication between two clusters in different zonesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoMap-Reduce pattern can be built with XAP task executorsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)none
Foreign keys infoReferential integrityyes infoRelationships in graphsnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDAtomic single-row operationsnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesnoyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyesyes 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.yesnono
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Role-based access controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nono

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More resources
Amazon NeptuneGigaSpacesGoogle Cloud BigtablemSQL infoMini SQLSphinx
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