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DBMS > Amazon Neptune vs. CockroachDB vs. Microsoft Azure Table Storage vs. Spark SQL

System Properties Comparison Amazon Neptune vs. CockroachDB vs. Microsoft Azure Table Storage vs. Spark SQL

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonCockroachDB  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonSpark SQL  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.A Wide Column Store for rapid development using massive semi-structured datasetsSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelGraph DBMS
RDF store
Relational DBMSWide column storeRelational 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
Score5.73
Rank#58  Overall
#34  Relational DBMS
Score4.04
Rank#77  Overall
#6  Wide column stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­neptunewww.cockroachlabs.comazure.microsoft.com/­en-us/­services/­storage/­tablesspark.apache.org/­sql
Technical documentationaws.amazon.com/­neptune/­developer-resourceswww.cockroachlabs.com/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonCockroach LabsMicrosoftApache Software Foundation
Initial release2017201520122014
Current release24.1.0, May 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0, commercial license availablecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoScala
Server operating systemshostedLinux
macOS
Windows
hostedLinux
OS X
Windows
Data schemeschema-freedynamic schemaschema-freeyes
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 indexesnoyesnono
SQL infoSupport of SQLnoyes, wire compatible with PostgreSQLnoSQL-like DML and DDL statements
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBCRESTful HTTP APIJDBC
ODBC
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresnononono
Triggersnononono
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 infoImplicit feature of the cloud serviceyes, utilizing Spark Core
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 RAFTyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDoptimistic lockingno
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)Role-based access controlAccess rights based on private key authentication or shared access signaturesno

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More resources
Amazon NeptuneCockroachDBMicrosoft Azure Table StorageSpark SQL
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