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DBMS > Amazon Neptune vs. CockroachDB vs. CrateDB

System Properties Comparison Amazon Neptune vs. CockroachDB vs. CrateDB

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonCockroachDB  Xexclude from comparisonCrateDB  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudCockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.Distributed Database based on Lucene
Primary database modelGraph DBMS
RDF store
Relational DBMSDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.58
Rank#112  Overall
#9  Graph DBMS
#5  RDF stores
Score6.10
Rank#58  Overall
#33  Relational DBMS
Score0.73
Rank#229  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Websiteaws.amazon.com/­neptunewww.cockroachlabs.comcratedb.com
Technical documentationaws.amazon.com/­neptune/­developer-resourceswww.cockroachlabs.com/­docscratedb.com/­docs
DeveloperAmazonCockroach LabsCrate
Initial release201720152013
Current release23.1.1, May 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0, commercial license availableOpen Source
Cloud-based only infoOnly available as a cloud serviceyesnono
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 languageGoJava
Server operating systemshostedLinux
macOS
Windows
All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support
Data schemeschema-freedynamic schemaFlexible Schema (defined schema, partial schema, schema free)
Typing infopredefined data types such as float or dateyesyesyes
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 indexesnoyesyes
SQL infoSupport of SQLnoyes, wire compatible with PostgreSQLyes, but no triggers and constraints, and PostgreSQL compatibility
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++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
.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 proceduresnonouser defined functions (Javascript)
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning (by key range) infoall tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFTSharding
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 using RAFTConfigurable replication on table/partition-level
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Read-after-write consistency on record level
Foreign keys infoReferential integrityyes infoRelationships in graphsyesno
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 strategy
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Role-based access controlrights management via user accounts
More information provided by the system vendor
Amazon NeptuneCockroachDBCrateDB
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 NeptuneCockroachDBCrateDB
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