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DBMS > Amazon Neptune vs. Faircom DB vs. Sphinx vs. TerminusDB

System Properties Comparison Amazon Neptune vs. Faircom DB vs. Sphinx vs. TerminusDB

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonSphinx  Xexclude from comparisonTerminusDB infoformer name was DataChemist  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Open source search engine for searching in data from different sources, e.g. relational databasesScalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships
Primary database modelGraph DBMS
RDF store
Key-value store
Relational DBMS
Search engineGraph DBMS
Secondary database modelsDocument store
RDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.20
Rank#119  Overall
#9  Graph DBMS
#5  RDF stores
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score0.17
Rank#325  Overall
#29  Graph DBMS
Websiteaws.amazon.com/­neptunewww.faircom.com/­products/­faircom-dbsphinxsearch.comterminusdb.com
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlsphinxsearch.com/­docsterminusdb.github.io/­terminusdb/­#
DeveloperAmazonFairCom CorporationSphinx Technologies Inc.DataChemist Ltd.
Initial release2017197920012018
Current releaseV12, November 20203.5.1, February 202311.0.0, January 2023
License infoCommercial or Open Sourcecommercialcommercial infoRestricted, free version availableOpen Source infoGPL version 2, commercial licence availableOpen Source infoGPL V3
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageANSI C, C++C++Prolog, Rust
Server operating systemshostedAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
Data schemeschema-freeschema free, schema optional, schema required, partial schema,yesyes
Typing infopredefined data types such as float or dateyesyes, ANSI SQL Types, JSON, typed binary structuresnoyes
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 indexesnoyesyes infofull-text index on all search fields
SQL infoSupport of SQLnoyes, ANSI SQL with proprietary extensionsSQL-like query language (SphinxQL)SQL-like query language (WOQL)
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
Proprietary protocolOWL
RESTful HTTP API
WOQL (Web Object Query Language)
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
JavaScript
Python
Server-side scripts infoStored proceduresnoyes info.Net, JavaScript, C/C++noyes
Triggersnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesnoneFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningSharding infoPartitioning is done manually, search queries against distributed index is supportedGraph Partitioning
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.yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).noneJournaling Streams
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Foreign keys infoReferential integrityyes infoRelationships in graphsyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDtunable from ACID to Eventually ConsistentnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restYes, tunable from durable to delayed durability to in-memoryyes infoThe original contents of fields are not stored in the Sphinx index.yes infoin-memory journaling
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Fine grained access rights according to SQL-standard with additional protections for filesnoRole-based access control

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More resources
Amazon NeptuneFaircom DB infoformerly c-treeACESphinxTerminusDB infoformer name was DataChemist
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