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DBMS > Amazon DocumentDB vs. Amazon Neptune vs. RavenDB vs. Sphinx vs. Splice Machine

System Properties Comparison Amazon DocumentDB vs. Amazon Neptune vs. RavenDB vs. Sphinx vs. Splice Machine

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonAmazon Neptune  Xexclude from comparisonRavenDB  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceFast, reliable graph database built for the cloudOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseOpen source search engine for searching in data from different sources, e.g. relational databasesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelDocument storeGraph DBMS
RDF store
Document storeSearch engineRelational DBMS
Secondary database modelsGraph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score2.20
Rank#119  Overall
#9  Graph DBMS
#5  RDF stores
Score2.92
Rank#101  Overall
#18  Document stores
Score5.98
Rank#56  Overall
#5  Search engines
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websiteaws.amazon.com/­documentdbaws.amazon.com/­neptuneravendb.netsphinxsearch.comsplicemachine.com
Technical documentationaws.amazon.com/­documentdb/­resourcesaws.amazon.com/­neptune/­developer-resourcesravendb.net/­docssphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperAmazonHibernating RhinosSphinx Technologies Inc.Splice Machine
Initial release20192017201020012014
Current release5.4, July 20223.5.1, February 20233.1, March 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoAGPL version 3, commercial license availableOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#C++Java
Server operating systemshostedhostedLinux
macOS
Raspberry Pi
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesnonoyes
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
Secondary indexesyesnoyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnonoSQL-like query language (RQL)SQL-like query language (SphinxQL)yes
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnonoyesnoyes infoJava
Triggersnonoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesnonenoneShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasMulti-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 replicationnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)noyesnoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.Immediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyes infoRelationships in graphsnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDACID, Cluster-wide transaction availablenoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyes infowith encyption-at-restyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
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 rolesAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Authorization levels configured per client per databasenoAccess rights for users, groups and roles according to SQL-standard

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More resources
Amazon DocumentDBAmazon NeptuneRavenDBSphinxSplice Machine
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