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DBMS > Badger vs. Datomic vs. Google Cloud Bigtable vs. IBM Db2 Event Store

System Properties Comparison Badger vs. Datomic vs. Google Cloud Bigtable vs. IBM Db2 Event Store

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Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonDatomic  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Distributed Event Store optimized for Internet of Things use cases
Primary database modelKey-value storeRelational DBMSKey-value store
Wide column store
Event Store
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#331  Overall
#49  Key-value stores
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Websitegithub.com/­dgraph-io/­badgerwww.datomic.comcloud.google.com/­bigtablewww.ibm.com/­products/­db2-event-store
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerdocs.datomic.comcloud.google.com/­bigtable/­docswww.ibm.com/­docs/­en/­db2-event-store
DeveloperDGraph LabsCognitectGoogleIBM
Initial release2017201220152017
Current release1.0.6735, June 20232.0
License infoCommercial or Open SourceOpen Source infoApache 2.0commercial infolimited edition freecommercialcommercial infofree developer edition available
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoJava, ClojureC and C++
Server operating systemsBSD
Linux
OS X
Solaris
Windows
All OS with a Java VMhostedLinux infoLinux, macOS, Windows for the developer addition
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or datenoyesnoyes
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.nononono
Secondary indexesnoyesnono
SQL infoSupport of SQLnononoyes infothrough the embedded Spark runtime
APIs and other access methodsRESTful HTTP APIgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
Supported programming languagesGoClojure
Java
C#
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
Server-side scripts infoStored proceduresnoyes infoTransaction Functionsnoyes
TriggersnoBy using transaction functionsnono
Partitioning methods infoMethods for storing different data on different nodesnonenone infoBut extensive use of caching in the application peersShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnonenone infoBut extensive use of caching in the application peersInternal replication in Colossus, and regional replication between two clusters in different zonesActive-active shard replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDAtomic single-row operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesNo - written data is immutable
Durability infoSupport for making data persistentyesyes 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 storage
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes inforecommended only for testing and developmentnoyes
User concepts infoAccess controlnonoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standard

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More resources
BadgerDatomicGoogle Cloud BigtableIBM Db2 Event Store
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