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

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

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonRavenDB  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparisonSqrrl  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceOpen 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 SparkAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelDocument storeDocument storeSearch engineRelational DBMSDocument store
Graph DBMS
Key-value store
Wide column store
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
Score2.92
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/­documentdbravendb.netsphinxsearch.comsplicemachine.comsqrrl.com
Technical documentationaws.amazon.com/­documentdb/­resourcesravendb.net/­docssphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperHibernating RhinosSphinx Technologies Inc.Splice MachineAmazon infooriginally Sqrrl Data, Inc.
Initial release20192010200120142012
Current release5.4, July 20223.5.1, February 20233.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoAGPL version 3, commercial license availableOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC#C++JavaJava
Server operating systemshostedLinux
macOS
Raspberry Pi
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Linux
Data schemeschema-freeschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyesnonoyesyes
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.no
Secondary indexesyesyesyes infofull-text index on all search fieldsyesyes
SQL infoSupport of SQLnoSQL-like query language (RQL)SQL-like query language (SphinxQL)yesno
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible).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
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
.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
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresnoyesnoyes infoJavano
Triggersnoyesnoyesno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar PartitioningSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasMulti-source replicationnoneMulti-source replication
Source-replica replication
selectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yesnoYes, via Full Spark Integrationyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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 ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACID, Cluster-wide transaction availablenoACIDAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yesyes
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 rolesAuthorization levels configured per client per databasenoAccess rights for users, groups and roles according to SQL-standardCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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More resources
Amazon DocumentDBRavenDBSphinxSplice MachineSqrrl
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