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DBMS > Google Cloud Datastore vs. Hive vs. IBM Db2 Event Store vs. Ignite

System Properties Comparison Google Cloud Datastore vs. Hive vs. IBM Db2 Event Store vs. Ignite

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHive  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonIgnite  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 HadoopDistributed Event Store optimized for Internet of Things use casesApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.
Primary database modelDocument storeRelational DBMSEvent Store
Time Series DBMS
Key-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.49
Rank#79  Overall
#12  Document stores
Score62.59
Rank#18  Overall
#12  Relational DBMS
Score0.23
Rank#316  Overall
#2  Event Stores
#28  Time Series DBMS
Score3.64
Rank#89  Overall
#13  Key-value stores
#48  Relational DBMS
Websitecloud.google.com/­datastorehive.apache.orgwww.ibm.com/­products/­db2-event-storeignite.apache.org
Technical documentationcloud.google.com/­datastore/­docscwiki.apache.org/­confluence/­display/­Hive/­Homewww.ibm.com/­docs/­en/­db2-event-storeapacheignite.readme.io/­docs
DeveloperGoogleApache Software Foundation infoinitially developed by FacebookIBMApache Software Foundation
Initial release2008201220172015
Current release3.1.3, April 20222.0Apache Ignite 2.6
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercial infofree developer edition availableOpen Source infoApache 2.0
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 and C++C++, Java, .Net
Server operating systemshostedAll OS with a Java VMLinux infoLinux, macOS, Windows for the developer additionLinux
OS X
Solaris
Windows
Data schemeschema-freeyesyesyes
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.nonoyes
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like DML and DDL statementsyes infothrough the embedded Spark runtimeANSI-99 for query and DML statements, subset of DDL
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
PHP
Python
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
C#
C++
Java
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresusing Google App Engineyes infouser defined functions and integration of map-reduceyesyes (compute grid and cache interceptors can be used instead)
TriggersCallbacks using the Google Apps Enginenonoyes (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 factorActive-active shard replicationyes (replicated cache)
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyes infoquery execution via MapReducenoyes (compute grid and hadoop accelerator)
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 ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesNo - written data is immutableyes
Durability infoSupport for making data persistentyesyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyes
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 rolesfine grained access rights according to SQL-standardSecurity Hooks for custom implementations

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More resources
Google Cloud DatastoreHiveIBM Db2 Event StoreIgnite
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