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DBMS > Google Cloud Datastore vs. Hive vs. Ignite vs. Nebula Graph

System Properties Comparison Google Cloud Datastore vs. Hive vs. Ignite vs. Nebula Graph

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHive  Xexclude from comparisonIgnite  Xexclude from comparisonNebula Graph  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platformdata warehouse software for querying and managing large distributed datasets, built on HadoopApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.A distributed, linear scalable, high perfomant Graph DBMS
Primary database modelDocument storeRelational DBMSKey-value store
Relational DBMS
Graph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.98
Rank#77  Overall
#11  Document stores
Score83.31
Rank#14  Overall
#9  Relational DBMS
Score6.38
Rank#64  Overall
#9  Key-value stores
#35  Relational DBMS
Score1.14
Rank#164  Overall
#15  Graph DBMS
Websitecloud.google.com/­datastorehive.apache.orgignite.apache.orggithub.com/­vesoft-inc/­nebula
nebula-graph.io
Technical documentationcloud.google.com/­datastore/­docscwiki.apache.org/­confluence/­display/­Hive/­Homeapacheignite.readme.io/­docsdocs.nebula-graph.io
DeveloperGoogleApache Software Foundation infoinitially developed by FacebookApache Software FoundationVesoft Inc.
Initial release2008201220152019
Current release3.1.2, August 2019Apache Ignite 2.6
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2Open Source infoApache 2.0Open Source infoApache Version 2.0 + Common Clause 1.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++, Java, .NetC++
Server operating systemshostedAll OS with a Java VMLinux
OS X
Solaris
Windows
Linux
Data schemeschema-freeyesyesStrong typed schema
Typing infopredefined data types such as float or dateyes, details hereyesyesyes
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 indexesyesyesyesyes infoNebula Graph internally uses the Key-Value store RocksDB for persistency. The vertices, edges, and their properties are stored as Key while their values are stored as Value. The primary indexes are per Key and secondary indexes are per Value.
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like DML and DDL statementsANSI-99 for query and DML statements, subset of DDLSQL-like query language
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Browser interface
console (shell)
Proprietary native API
Query language nGQL
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
PHP
Python
C#
C++
Java
PHP
Python
Ruby
Scala
C++
Go
Java
Python
Server-side scripts infoStored proceduresusing Google App Engineyes infouser defined functions and integration of map-reduceyes (compute grid and cache interceptors can be used instead)
TriggersCallbacks using the Google Apps Enginenoyes (cache interceptors and events)
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosselectable replication factoryes (replicated cache)Causal Clustering using Raft protocol
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyes infoquery execution via MapReduceyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Eventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnonoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infousing RocksDB
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, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and rolesSecurity Hooks for custom implementationsRole-based access control
More information provided by the system vendor
Google Cloud DatastoreHiveIgniteNebula Graph
News

How to Select a Graph Database: Best Practices at RoyalFlush
17 November 2021

Nebula Hackathon 2021 is live now!
16 November 2021

Nebula Graph v2.6.0 Performance Report
12 November 2021

Introducing TOSS: Achieving Eventual Consistency of Edges in Nebula Graph
11 November 2021

Nebula Graph v2.6 Release Note
8 November 2021

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