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DBMS > Amazon Neptune vs. CrateDB vs. Pinecone vs. YDB

System Properties Comparison Amazon Neptune vs. CrateDB vs. Pinecone vs. YDB

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonCrateDB  Xexclude from comparisonPinecone  Xexclude from comparisonYDB  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudDistributed Database based on LuceneA managed, cloud-native vector databaseA distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API
Primary database modelGraph DBMS
RDF store
Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Vector DBMSDocument store
Relational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.20
Rank#119  Overall
#9  Graph DBMS
#5  RDF stores
Score0.73
Rank#224  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score3.16
Rank#95  Overall
#2  Vector DBMS
Score0.35
Rank#278  Overall
#43  Document stores
#127  Relational DBMS
Websiteaws.amazon.com/­neptunecratedb.comwww.pinecone.iogithub.com/­ydb-platform/­ydb
ydb.tech
Technical documentationaws.amazon.com/­neptune/­developer-resourcescratedb.com/­docsdocs.pinecone.io/­docs/­overviewydb.tech/­en/­docs
DeveloperAmazonCratePinecone Systems, IncYandex
Initial release2017201320192019
License infoCommercial or Open SourcecommercialOpen SourcecommercialOpen Source infoApache 2.0; commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform.
Implementation languageJava
Server operating systemshostedAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supporthostedLinux
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)Flexible Schema (defined schema, partial schema, schema free)
Typing infopredefined data types such as float or dateyesyesString, 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.nononono
Secondary indexesnoyesyes
SQL infoSupport of SQLnoyes, but no triggers and constraints, and PostgreSQL compatibilitynoSQL-like query language (YQL)
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
RESTful HTTP APIRESTful HTTP API (DynamoDB compatible)
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
.NET
Erlang
Go infocommunity maintained client
Java
JavaScript (Node.js) infocommunity maintained client
Perl infocommunity maintained client
PHP
Python
R
Ruby infocommunity maintained client
Scala infocommunity maintained client
PythonGo
Java
JavaScript (Node.js)
PHP
Python
Server-side scripts infoStored proceduresnouser defined functions (Javascript)no
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding
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.Configurable replication on table/partition-levelActive-passive shard replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Read-after-write consistency on record level
Immediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno infounique row identifiers can be used for implementing an optimistic concurrency control strategyACID
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.nonono
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)rights management via user accountsAccess rights defined for Yandex Cloud users
More information provided by the system vendor
Amazon NeptuneCrateDBPineconeYDB
Specific characteristicsThe enterprise database for time series, documents, and vectors. Distributed - Native...
» more
Competitive advantagesResponse time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
» more
Typical application scenarios​ IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
» more
Key customersAcross all continents, CrateDB is used by companies of all sizes to meet the most...
» more
Market metricsThe CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
» more
Licensing and pricing modelsSee CrateDB pricing >
» more

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More resources
Amazon NeptuneCrateDBPineconeYDB
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