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DBMS > Amazon Neptune vs. CrateDB vs. Databend vs. Hive

System Properties Comparison Amazon Neptune vs. CrateDB vs. Databend vs. Hive

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonCrateDB  Xexclude from comparisonDatabend  Xexclude from comparisonHive  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudDistributed Database based on LuceneAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexitydata warehouse software for querying and managing large distributed datasets, built on Hadoop
Primary database modelGraph DBMS
RDF store
Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMSRelational 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
Score0.30
Rank#287  Overall
#130  Relational DBMS
Score61.17
Rank#18  Overall
#12  Relational DBMS
Websiteaws.amazon.com/­neptunecratedb.comgithub.com/­datafuselabs/­databend
www.databend.com
hive.apache.org
Technical documentationaws.amazon.com/­neptune/­developer-resourcescratedb.com/­docsdocs.databend.comcwiki.apache.org/­confluence/­display/­Hive/­Home
DeveloperAmazonCrateDatabend LabsApache Software Foundation infoinitially developed by Facebook
Initial release2017201320212012
Current release1.0.59, April 20233.1.3, April 2022
License infoCommercial or Open SourcecommercialOpen SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2
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 languageJavaRustJava
Server operating systemshostedAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supporthosted
Linux
macOS
All OS with a Java VM
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)yesyes
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.nonono
Secondary indexesnoyesnoyes
SQL infoSupport of SQLnoyes, but no triggers and constraints, and PostgreSQL compatibilityyesSQL-like DML and DDL statements
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
CLI Client
JDBC
RESTful HTTP API
JDBC
ODBC
Thrift
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
Go
Java
JavaScript (Node.js)
Python
Rust
C++
Java
PHP
Python
Server-side scripts infoStored proceduresnouser defined functions (Javascript)noyes infouser defined functions and integration of map-reduce
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingnoneSharding
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-levelnoneselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes infoquery execution via MapReduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Read-after-write consistency on record level
Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnonono
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 strategyyesno
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)rights management via user accountsUsers with fine-grained authorization concept, user rolesAccess rights for users, groups and roles
More information provided by the system vendor
Amazon NeptuneCrateDBDatabendHive
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 NeptuneCrateDBDatabendHive
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