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DBMS > Amazon DocumentDB vs. Apache Impala vs. GigaSpaces vs. JanusGraph vs. Sphinx

System Properties Comparison Amazon DocumentDB vs. Apache Impala vs. GigaSpaces vs. JanusGraph vs. Sphinx

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonApache Impala  Xexclude from comparisonGigaSpaces  Xexclude from comparisonJanusGraph infosuccessor of Titan  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceAnalytic DBMS for HadoopHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsA Graph DBMS optimized for distributed clusters infoIt was forked from the latest code base of Titan in January 2017Open source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeRelational DBMSDocument store
Object oriented DBMS infoValues are user defined objects
Graph DBMSSearch engine
Secondary database modelsDocument storeGraph DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score1.94
Rank#129  Overall
#12  Graph DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websiteaws.amazon.com/­documentdbimpala.apache.orgwww.gigaspaces.comjanusgraph.orgsphinxsearch.com
Technical documentationaws.amazon.com/­documentdb/­resourcesimpala.apache.org/­impala-docs.htmldocs.gigaspaces.com/­latest/­landing.htmldocs.janusgraph.orgsphinxsearch.com/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGigaspaces TechnologiesLinux Foundation; originally developed as Titan by AureliusSphinx Technologies Inc.
Initial release20192013200020172001
Current release4.1.0, June 202215.5, September 20200.6.3, February 20233.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2Open Source infoApache Version 2; Commercial licenses availableOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java, C++, .NetJavaC++
Server operating systemshostedLinuxLinux
macOS
Solaris
Windows
Linux
OS X
Unix
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesyesno
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 infoXML can be used for describing objects metadatano
Secondary indexesyesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLnoSQL-like DML and DDL statementsSQL-99 for query and DML statementsnoSQL-like query language (SphinxQL)
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBC
ODBC
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
Proprietary protocol
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
All languages supporting JDBC/ODBC.Net
C++
Java
Python
Scala
Clojure
Java
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reduceyesyesno
Triggersnonoyes, event driven architectureyesno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingyes infodepending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)Sharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasselectable replication factorMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
yesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yes infoquery execution via MapReduceyes infoMap-Reduce pattern can be built with XAP task executorsyes infovia Faunus, a graph analytics engineno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenonoyes infoRelationships in graphsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsnoACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcastyes 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.noyes
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users, groups and roles infobased on Apache Sentry and KerberosRole-based access controlUser authentification and security via Rexster Graph Serverno

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More resources
Amazon DocumentDBApache ImpalaGigaSpacesJanusGraph infosuccessor of TitanSphinx
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