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DBMS > Amazon Neptune vs. Google Cloud Bigtable vs. GridGain vs. NSDb vs. RisingWave

System Properties Comparison Amazon Neptune vs. Google Cloud Bigtable vs. GridGain vs. NSDb vs. RisingWave

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonGridGain  Xexclude from comparisonNSDb  Xexclude from comparisonRisingWave  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.GridGain is an in-memory computing platform, built on Apache IgniteScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesA distributed RDBMS for stream processing, wire-compatible with PostgreSQL
Primary database modelGraph DBMS
RDF store
Key-value store
Wide column store
Key-value store
Relational DBMS
Time Series DBMSRelational 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
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score0.58
Rank#242  Overall
#111  Relational DBMS
Websiteaws.amazon.com/­neptunecloud.google.com/­bigtablewww.gridgain.comnsdb.iowww.risingwave.com/­database
Technical documentationaws.amazon.com/­neptune/­developer-resourcescloud.google.com/­bigtable/­docswww.gridgain.com/­docs/­index.htmlnsdb.io/­Architecturedocs.risingwave.com/­docs/­current/­intro
DeveloperAmazonGoogleGridGain Systems, Inc.RisingWave Labs
Initial release20172015200720172022
Current releaseGridGain 8.5.11.2, September 2023
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache Version 2.0Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, C++, .NetJava, ScalaRust
Server operating systemshostedhostedLinux
OS X
Solaris
Windows
Linux
macOS
Docker
Linux
macOS
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyesyes: int, bigint, decimal, stringStandard SQL-types and JSON
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.nonoyesnono
Secondary indexesnonoyesall fields are automatically indexedyes
SQL infoSupport of SQLnonoANSI-99 for query and DML statements, subset of DDLSQL-like query languageyes
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
gRPC
HTTP REST
WebSocket
JDBC
PostgreSQL wire protocol
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
C#
C++
Java
PHP
Python
Ruby
Scala
Java
Scala
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnonoyes (compute grid and cache interceptors can be used instead)noUDFs in Python or Java
Triggersnonoyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding
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.Internal replication in Colossus, and regional replication between two clusters in different zonesyes (replicated cache)
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes (compute grid and hadoop accelerator)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesUsing Apache Luceneyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
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 (IAM)Security Hooks for custom implementationsUsers and Roles

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More resources
Amazon NeptuneGoogle Cloud BigtableGridGainNSDbRisingWave
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