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DBMS > Amazon Neptune vs. Axibase vs. BaseX vs. Vertica

System Properties Comparison Amazon Neptune vs. Axibase vs. BaseX vs. Vertica

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonAxibase  Xexclude from comparisonBaseX  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudScalable TimeSeries DBMS based on HBase with integrated rule engine and visualizationLight-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.Cloud 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 DBMS
RDF store
Time Series DBMSNative XML DBMSRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.20
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score0.21
Rank#308  Overall
#25  Time Series DBMS
Score1.56
Rank#141  Overall
#4  Native XML DBMS
Score9.62
Rank#42  Overall
#26  Relational DBMS
Websiteaws.amazon.com/­neptuneaxibase.com/­docs/­atsd/­financebasex.orgwww.vertica.com
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.basex.orgvertica.com/­documentation
DeveloperAmazonAxibase CorporationBaseX GmbHOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2017201320072005
Current release1558511.2, August 202412.0.3, January 2023
License infoCommercial or Open Sourcecommercialcommercial infoCommunity Edition (single node) is free, Enterprise Edition (distributed) is paidOpen Source infoBSD licensecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud serviceyesnonono 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 languageJavaJavaC++
Server operating systemshostedLinuxLinux
OS X
Windows
Linux
Data schemeschema-freeyesschema-freeYes, 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 dateyesyes infoshort, integer, long, float, double, decimal, stringno infoXQuery supports typesyes
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 indexesnonoyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnoSQL-like query languagenoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBC
Proprietary protocol (Network API)
RESTful HTTP API
Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
Go
Java
PHP
Python
R
Ruby
Actionscript
C
C#
Haskell
Java
JavaScript infoNode.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnoyesyesyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyesyes infovia eventsyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesnoneShardingnonehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-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.Source-replica replicationnoneMulti-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 methodsnoyesnono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnomultiple readers, single writerACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Users with fine-grained authorization concept on 4 levelsfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

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More resources
Amazon NeptuneAxibaseBaseXVertica infoOpenText™ Vertica™
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