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DBMS > Amazon DocumentDB vs. GBase vs. Pinecone vs. Splice Machine

System Properties Comparison Amazon DocumentDB vs. GBase vs. Pinecone vs. Splice Machine

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonGBase  Xexclude from comparisonPinecone  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceWidely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.A managed, cloud-native vector databaseOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelDocument storeRelational DBMSVector DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score1.07
Rank#185  Overall
#86  Relational DBMS
Score3.16
Rank#95  Overall
#2  Vector DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websiteaws.amazon.com/­documentdbwww.gbase.cnwww.pinecone.iosplicemachine.com
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.pinecone.io/­docs/­overviewsplicemachine.com/­how-it-works
DeveloperGeneral Data Technology Co., Ltd.Pinecone Systems, IncSplice Machine
Initial release2019200420192014
Current releaseGBase 8a, GBase 8s, GBase 8c3.1, March 2021
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, Java, PythonJava
Server operating systemshostedLinuxhostedLinux
OS X
Solaris
Windows
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesString, Number, Booleanyes
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.noyesno
Secondary indexesyesyesyes
SQL infoSupport of SQLnoStandard with numerous extensionsnoyes
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)ADO.NET
C API
JDBC
ODBC
RESTful HTTP APIJDBC
Native Spark Datasource
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C#PythonC#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnouser defined functionsyes infoJava
Triggersnoyesyes
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning (by range, list and hash) and vertical partitioningShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)noYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlAccess rights for users and rolesyesAccess rights for users, groups and roles according to SQL-standard

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More resources
Amazon DocumentDBGBasePineconeSplice Machine
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