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DBMS > Google Cloud Datastore vs. Hypertable vs. IBM Db2 Event Store vs. Netezza

System Properties Comparison Google Cloud Datastore vs. Hypertable vs. IBM Db2 Event Store vs. Netezza

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHypertable  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformAn open source BigTable implementation based on distributed file systems such as HadoopDistributed Event Store optimized for Internet of Things use casesData warehouse and analytics appliance part of IBM PureSystems
Primary database modelDocument storeWide column storeEvent Store
Time Series DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Websitecloud.google.com/­datastorewww.ibm.com/­products/­db2-event-storewww.ibm.com/­products/­netezza
Technical documentationcloud.google.com/­datastore/­docswww.ibm.com/­docs/­en/­db2-event-store
DeveloperGoogleHypertable Inc.IBMIBM
Initial release2008200920172000
Current release0.9.8.11, March 20162.0
License infoCommercial or Open SourcecommercialOpen Source infoGNU version 3. Commercial license availablecommercial infofree developer edition availablecommercial
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 languageC++C and C++
Server operating systemshostedLinux
OS X
Windows infoan inofficial Windows port is available
Linux infoLinux, macOS, Windows for the developer additionLinux infoincluded in appliance
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyes, details herenoyesyes
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 indexesyesrestricted infoonly exact value or prefix value scansnoyes
SQL infoSupport of SQLSQL-like query language (GQL)noyes infothrough the embedded Spark runtimeyes
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
C++ API
Thrift
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
OLE DB
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
Perl
PHP
Python
Ruby
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
C
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresusing Google App Enginenoyesyes
TriggersCallbacks using the Google Apps Enginenonono
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 factor on file system levelActive-active shard replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyesnoyes
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.Immediate ConsistencyEventual 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.noyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nofine grained access rights according to SQL-standardUsers with fine-grained authorization concept

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More resources
Google Cloud DatastoreHypertableIBM Db2 Event StoreNetezza infoAlso called PureData System for Analytics by IBM
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