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DBMS > Amazon Neptune vs. Apache Phoenix vs. CrateDB vs. SpatiaLite

System Properties Comparison Amazon Neptune vs. Apache Phoenix vs. CrateDB vs. SpatiaLite

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonApache Phoenix  Xexclude from comparisonCrateDB  Xexclude from comparisonSpatiaLite  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudA scale-out RDBMS with evolutionary schema built on Apache HBaseDistributed Database based on LuceneSpatial extension of SQLite
Primary database modelGraph DBMS
RDF store
Relational DBMSDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Spatial DBMS
Secondary database modelsRelational DBMSRelational 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
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score0.73
Rank#224  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score1.60
Rank#149  Overall
#3  Spatial DBMS
Websiteaws.amazon.com/­neptunephoenix.apache.orgcratedb.comwww.gaia-gis.it/­fossil/­libspatialite/­index
Technical documentationaws.amazon.com/­neptune/­developer-resourcesphoenix.apache.orgcratedb.com/­docswww.gaia-gis.it/­gaia-sins/­spatialite_topics.html
DeveloperAmazonApache Software FoundationCrateAlessandro Furieri
Initial release2017201420132008
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20195.0.0, August 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open SourceOpen Source infoMPL 1.1, GPL v2.0 or LGPL v2.1
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 languageJavaJavaC++
Server operating systemshostedLinux
Unix
Windows
All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportserver-less
Data schemeschema-freeyes infolate-bound, schema-on-read capabilitiesFlexible Schema (defined schema, partial schema, schema free)yes
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 indexesnoyesyesyes
SQL infoSupport of SQLnoyesyes, but no triggers and constraints, and PostgreSQL compatibilityyes
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBCADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C
C#
C++
Go
Groovy
Java
PHP
Python
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 functionsuser defined functions (Javascript)no
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingnone
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
Source-replica replication
Configurable replication on table/partition-levelnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoHadoop integrationnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyEventual Consistency
Read-after-write consistency on record level
Foreign keys infoReferential integrityyes infoRelationships in graphsnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno 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.yesnoyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyrights management via user accountsno
More information provided by the system vendor
Amazon NeptuneApache PhoenixCrateDBSpatiaLite
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 NeptuneApache PhoenixCrateDBSpatiaLite
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