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DBMS > AllegroGraph vs. Amazon DocumentDB vs. Apache IoTDB vs. Sphinx vs. Splice Machine

System Properties Comparison AllegroGraph vs. Amazon DocumentDB vs. Apache IoTDB vs. Sphinx vs. Splice Machine

Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonAmazon DocumentDB  Xexclude from comparisonApache IoTDB  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionHigh performance, persistent RDF store with additional support for Graph DBMSFast, scalable, highly available, and fully managed MongoDB-compatible database serviceAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkOpen 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 store infowith version 6.5
Graph DBMS
RDF store
Vector DBMS
Document storeTime Series DBMSSearch engineRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.06
Rank#187  Overall
#30  Document stores
#17  Graph DBMS
#7  RDF stores
#7  Vector DBMS
Score1.91
Rank#132  Overall
#24  Document stores
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websiteallegrograph.comaws.amazon.com/­documentdbiotdb.apache.orgsphinxsearch.comsplicemachine.com
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmlaws.amazon.com/­documentdb/­resourcesiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlsphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperFranz Inc.Apache Software FoundationSphinx Technologies Inc.Splice Machine
Initial release20042019201820012014
Current release8.0, December 20231.1.0, April 20233.5.1, February 20233.1, March 2021
License infoCommercial or Open Sourcecommercial infoLimited community edition freecommercialOpen Source infoApache Version 2.0Open Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++Java
Server operating systemsLinux
OS X
Windows
hostedAll OS with a Java VM (>= 1.8)FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeyes infoRDF schemasschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyesyesnoyes
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 infobulk load of XML files possiblenono
Secondary indexesyesyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLSPARQL is used as query languagenoSQL-like query languageSQL-like query language (SphinxQL)yes
APIs and other access methodsRESTful HTTP API
SPARQL
proprietary protocol using JSON (MongoDB compatible)JDBC
Native API
Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languagesC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
Go
Java
JavaScript (Node.js)
PHP
Python
C
C#
C++
Go
Java
Python
Scala
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 proceduresyes infoJavaScript or Common Lispnoyesnoyes infoJava
Triggersyesnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodeswith Federationnonehorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding 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-source replication
Source-replica replication
Multi-availability zones for high availability, asynchronous replication for up to 15 read replicasselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)Integration with Hadoop and SparknoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyEventual Consistency
Strong Consistency with Raft
Immediate Consistency
Foreign keys infoReferential integritynono infotypically not used, however similar functionality with DBRef possiblenonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-document operationsnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes 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.noyesyes
User concepts infoAccess controlUsers with fine-grained authorization concept, user roles and pluggable authenticationAccess rights for users and rolesyesnoAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
AllegroGraphAmazon DocumentDBApache IoTDBSphinxSplice Machine
Specific characteristicsKnowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
» more
Competitive advantagesAllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and...
» more
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