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DBMS > Datomic vs. Google Cloud Firestore vs. IBM Db2 Event Store vs. Netezza

System Properties Comparison Datomic vs. Google Cloud Firestore vs. IBM Db2 Event Store vs. Netezza

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityCloud 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.Distributed Event Store optimized for Internet of Things use casesData warehouse and analytics appliance part of IBM PureSystems
Primary database modelRelational DBMSDocument storeEvent Store
Time Series DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score7.85
Rank#51  Overall
#8  Document stores
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Websitewww.datomic.comfirebase.google.com/­products/­firestorewww.ibm.com/­products/­db2-event-storewww.ibm.com/­products/­netezza
Technical documentationdocs.datomic.comfirebase.google.com/­docs/­firestorewww.ibm.com/­docs/­en/­db2-event-store
DeveloperCognitectGoogleIBMIBM
Initial release2012201720172000
Current release1.0.6735, June 20232.0
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialcommercial infofree developer edition availablecommercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureC and C++
Server operating systemsAll OS with a Java VMhostedLinux infoLinux, macOS, Windows for the developer additionLinux infoincluded in appliance
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.nonono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLnonoyes infothrough the embedded Spark runtimeyes
APIs and other access methodsRESTful HTTP APIAndroid
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
OLE DB
Supported programming languagesClojure
Java
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
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 proceduresyes infoTransaction Functionsyes, Firebase Rules & Cloud Functionsyesyes
TriggersBy using transaction functionsyes, with Cloud Functionsnono
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersMulti-source replicationActive-active shard replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoUsing Cloud Dataflownoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesNo - written data is immutableyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesYes - 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.yes inforecommended only for testing and developmentyes
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.fine grained access rights according to SQL-standardUsers with fine-grained authorization concept

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More resources
DatomicGoogle Cloud FirestoreIBM Db2 Event StoreNetezza infoAlso called PureData System for Analytics by IBM
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