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DBMS > Amazon Neptune vs. CockroachDB vs. EDB Postgres vs. Spark SQL vs. Yaacomo

System Properties Comparison Amazon Neptune vs. CockroachDB vs. EDB Postgres vs. Spark SQL vs. Yaacomo

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonCockroachDB  Xexclude from comparisonEDB Postgres  Xexclude from comparisonSpark SQL  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
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.The EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.Spark SQL is a component on top of 'Spark Core' for structured data processingOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelGraph DBMS
RDF store
Relational DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial 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
Score6.15
Rank#55  Overall
#33  Relational DBMS
Score1.90
Rank#135  Overall
#63  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­neptunewww.cockroachlabs.comwww.enterprisedb.comspark.apache.org/­sqlyaacomo.com
Technical documentationaws.amazon.com/­neptune/­developer-resourceswww.cockroachlabs.com/­docswww.enterprisedb.com/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonCockroach LabsEnterpriseDBApache Software FoundationQ2WEB GmbH
Initial release20172015200520142009
Current release24.1.0, May 202414, December 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0, commercial license availablecommercial infoBSD for PostgreSQL-componentsOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoCScala
Server operating systemshostedLinux
macOS
Windows
Linux
Windows
Linux
OS X
Windows
Android
Linux
Windows
Data schemeschema-freedynamic schemayesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.nonoyes infospecific XML-type available, but no XML query functionality.nono
Secondary indexesnoyesyesnoyes
SQL infoSupport of SQLnoyes, wire compatible with PostgreSQLyes infostandard with numerous extensionsSQL-like DML and DDL statementsyes
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBCADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
JDBC
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++
Delphi
Java
Perl
PHP
Python
Tcl
Java
Python
R
Scala
Server-side scripts infoStored proceduresnonouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.no
Triggersnonoyesnoyes
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 RAFThorizontal partitioning infoby hash, list or rangeyes, utilizing Spark Corehorizontal partitioning
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 RAFTMulti-source replicationnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsyesyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Role-based access controlfine grained access rights according to SQL-standardnofine grained access rights according to SQL-standard

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More resources
Amazon NeptuneCockroachDBEDB PostgresSpark SQLYaacomo
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