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DBMS > Amazon Neptune vs. LeanXcale vs. Pinecone vs. Vertica

System Properties Comparison Amazon Neptune vs. LeanXcale vs. Pinecone vs. Vertica

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonLeanXcale  Xexclude from comparisonPinecone  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesA managed, cloud-native vector databaseCloud 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
Key-value store
Relational DBMS
Vector 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
Score0.28
Rank#286  Overall
#41  Key-value stores
#130  Relational DBMS
Score3.02
Rank#87  Overall
#3  Vector DBMS
Score9.62
Rank#42  Overall
#26  Relational DBMS
Websiteaws.amazon.com/­neptunewww.leanxcale.comwww.pinecone.iowww.vertica.com
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.pinecone.io/­docs/­overviewvertica.com/­documentation
DeveloperAmazonLeanXcalePinecone Systems, IncOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2017201520192005
Current release12.0.3, January 2023
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud serviceyesnoyesno 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 languageC++
Server operating systemshostedhostedLinux
Data schemeschema-freeyesYes, 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 dateyesString, Number, Booleanyes
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 indexesnoNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnoyes infothrough Apache DerbynoFull 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
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
RESTful HTTP APIADO.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
C
Java
Scala
PythonC#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal 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.Multi-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 methodsnononono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID
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.yesnono
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

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More resources
Amazon NeptuneLeanXcalePineconeVertica infoOpenText™ Vertica™
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