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DBMS > Amazon DocumentDB vs. Amazon Neptune vs. Splice Machine vs. SurrealDB

System Properties Comparison Amazon DocumentDB vs. Amazon Neptune vs. Splice Machine vs. SurrealDB

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonAmazon Neptune  Xexclude from comparisonSplice Machine  Xexclude from comparisonSurrealDB  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceFast, reliable graph database built for the cloudOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkA fully ACID transactional, developer-friendly, multi-model DBMS
Primary database modelDocument storeGraph DBMS
RDF store
Relational DBMSDocument store
Graph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.80
Rank#126  Overall
#24  Document stores
Score2.13
Rank#111  Overall
#9  Graph DBMS
#5  RDF stores
Score0.54
Rank#243  Overall
#114  Relational DBMS
Score1.08
Rank#176  Overall
#30  Document stores
#16  Graph DBMS
Websiteaws.amazon.com/­documentdbaws.amazon.com/­neptunesplicemachine.comsurrealdb.com
Technical documentationaws.amazon.com/­documentdb/­resourcesaws.amazon.com/­neptune/­developer-resourcessplicemachine.com/­how-it-workssurrealdb.com/­docs
DeveloperAmazonSplice MachineSurrealDB Ltd
Initial release2019201720142022
Current release3.1, March 2021v1.5.0, May 2024
License infoCommercial or Open SourcecommercialcommercialOpen Source infoAGPL 3.0, commercial license availableOpen Source
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaRust
Server operating systemshostedhostedLinux
OS X
Solaris
Windows
Linux
macOS
Windows
Data schemeschema-freeschema-freeyesschema-free
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.nono
Secondary indexesyesnoyes
SQL infoSupport of SQLnonoyesSQL-like query language
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBC
Native Spark Datasource
ODBC
GraphQL
RESTful HTTP API
WebSocket
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Deno
Go
JavaScript (Node.js)
Rust
Server-side scripts infoStored proceduresnonoyes infoJava
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesnonenoneShared 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 replicasMulti-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
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 Integrationno
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 possibleyes infoRelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyes infowith encyption-at-restyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access rights for users, groups and roles according to SQL-standardyes, based on authentication and database rules

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More resources
Amazon DocumentDBAmazon NeptuneSplice MachineSurrealDB
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