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DBMS > Amazon Neptune vs. Apache Kylin vs. CrateDB vs. Warp 10

System Properties Comparison Amazon Neptune vs. Apache Kylin vs. CrateDB vs. Warp 10

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonApache Kylin  Xexclude from comparisonCrateDB  Xexclude from comparisonWarp 10  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudA distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stackDistributed Database based on LuceneTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelGraph DBMS
RDF store
Relational DBMSDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Time Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.29
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score1.25
Rank#170  Overall
#77  Relational DBMS
Score0.71
Rank#227  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#9  Vector DBMS
Score0.14
Rank#344  Overall
#32  Time Series DBMS
Websiteaws.amazon.com/­neptunekylin.apache.orgcratedb.comwww.warp10.io
Technical documentationaws.amazon.com/­neptune/­developer-resourceskylin.apache.org/­docscratedb.com/­docswww.warp10.io/­content/­02_Getting_started
DeveloperAmazonApache Software Foundation, originally contributed from eBay IncCrateSenX
Initial release2017201520132015
Current release3.1.0, July 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open SourceOpen Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
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 languageJavaJavaJava
Server operating systemshostedLinuxAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportLinux
OS X
Windows
Data schemeschema-freeyesFlexible Schema (defined schema, partial schema, schema free)schema-free
Typing infopredefined data types such as float or dateyesyesyesyes
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 indexesnoyesyesno
SQL infoSupport of SQLnoANSI SQL for queries (using Apache Calcite)yes, but no triggers and constraints, and PostgreSQL compatibilityno
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
HTTP API
Jupyter
WebSocket
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
Server-side scripts infoStored proceduresnouser defined functions (Javascript)yes infoWarpScript
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infobased on HBase
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-levelselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Read-after-write consistency on record level
Immediate Consistency infobased on HBase
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 strategyno
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.nonoyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)rights management via user accountsMandatory use of cryptographic tokens, containing fine-grained authorizations
More information provided by the system vendor
Amazon NeptuneApache KylinCrateDBWarp 10
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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Amazon NeptuneApache KylinCrateDBWarp 10
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