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DBMS > Amazon Neptune vs. Google Cloud Firestore vs. LevelDB vs. openGauss vs. Splice Machine

System Properties Comparison Amazon Neptune vs. Google Cloud Firestore vs. LevelDB vs. openGauss vs. Splice Machine

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonLevelDB  Xexclude from comparisonopenGauss  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudCloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.Embeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesAn enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by HuaweiOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelGraph DBMS
RDF store
Document storeKey-value storeRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial 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
Score7.36
Rank#53  Overall
#9  Document stores
Score2.25
Rank#115  Overall
#19  Key-value stores
Score1.06
Rank#184  Overall
#84  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteaws.amazon.com/­neptunefirebase.google.com/­products/­firestoregithub.com/­google/­leveldbgitee.com/­opengauss
opengauss.org
splicemachine.com
Technical documentationaws.amazon.com/­neptune/­developer-resourcesfirebase.google.com/­docs/­firestoregithub.com/­google/­leveldb/­blob/­main/­doc/­index.mddocs.opengauss.org/­en
gitee.com/­opengauss/­docs
splicemachine.com/­how-it-works
DeveloperAmazonGoogleGoogleHuawei and openGauss communitySplice Machine
Initial release20172017201120192014
Current release1.23, February 20213.0, March 20223.1, March 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoBSDOpen SourceOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C, C++, JavaJava
Server operating systemshostedhostedIllumos
Linux
OS X
Windows
LinuxLinux
OS X
Solaris
Windows
Data schemeschema-freeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesnoyesyes
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 indexesnoyesnoyesyes
SQL infoSupport of SQLnononoANSI SQL 2011yes
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
C
C++
Java
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyes, Firebase Rules & Cloud Functionsnoyesyes infoJava
Triggersnoyes, with Cloud Functionsnoyesyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingnonehorizontal partitioning (by range, list and hash)Shared Nothhing Auto-Sharding, Columnar 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 replicationnoneSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoUsing Cloud DataflownonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyes infowith automatic compression on writesyesyes
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 roles can be defined via the AWS Identity and Access Management (IAM)Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.noAccess rights for users, groups and roles according to SQL-standardAccess rights for users, groups and roles according to SQL-standard

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More resources
Amazon NeptuneGoogle Cloud FirestoreLevelDBopenGaussSplice Machine
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