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DBMS > HugeGraph vs. Machbase Neo vs. Sphinx vs. Vertica

System Properties Comparison HugeGraph vs. Machbase Neo vs. Sphinx vs. Vertica

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Editorial information provided by DB-Engines
NameHugeGraph  Xexclude from comparisonMachbase Neo infoFormer name was Infiniflux  Xexclude from comparisonSphinx  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionA fast-speed and highly-scalable Graph DBMSTimeSeries DBMS for AIoT and BigDataOpen source search engine for searching in data from different sources, e.g. relational databasesCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelGraph DBMSTime Series DBMSSearch engineRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.17
Rank#335  Overall
#31  Graph DBMS
Score0.17
Rank#337  Overall
#30  Time Series DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitegithub.com/­hugegraph
hugegraph.apache.org
machbase.comsphinxsearch.comwww.vertica.com
Technical documentationhugegraph.apache.org/­docsmachbase.com/­dbmssphinxsearch.com/­docsvertica.com/­documentation
DeveloperBaiduMachbaseSphinx Technologies Inc.OpenText infopreviously Micro Focus and Hewlett Packard
Initial release2018201320012005
Current release0.9V8.0, August 20233.5.1, February 202312.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infofree test version availableOpen Source infoGPL version 2, commercial licence availablecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenononono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCC++C++
Server operating systemsLinux
macOS
Unix
Linux
macOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
Data schemeyesyesyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or dateyesyesnoyes
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 indexesyes infoalso supports composite index and range indexyesyes infofull-text index on all search fieldsNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnoSQL-like query languageSQL-like query language (SphinxQL)Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJava API
RESTful HTTP API
TinkerPop Gremlin
gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
Proprietary protocolADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesGroovy
Java
Python
C
C#
C++
Go
Java
JavaScript
PHP infovia ODBC
Python
R infovia ODBC
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresasynchronous Gremlin script jobsnonoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnononoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesyes infodepending on used storage backend, e.g. Cassandra and HBaseShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedhorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes infodepending on used storage backend, e.g. Cassandra and HBaseselectable replication factornoneMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsvia hugegraph-sparknonono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoedges in graphnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesnoyes 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.yesyes infovolatile and lookup tableno
User concepts infoAccess controlUsers, roles and permissionssimple password-based access controlnofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
HugeGraphMachbase Neo infoFormer name was InfinifluxSphinxVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
» more

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More resources
HugeGraphMachbase Neo infoFormer name was InfinifluxSphinxVertica infoOpenText™ Vertica™
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