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

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

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonDatomic  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonQuasardb  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 durabilityAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformDistributed Event Store optimized for Internet of Things use casesDistributed, high-performance timeseries database
Primary database modelKey-value storeRelational DBMSDocument storeEvent Store
Time Series DBMS
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
Score4.47
Rank#76  Overall
#12  Document stores
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Websitegithub.com/­dgraph-io/­badgerwww.datomic.comcloud.google.com/­datastorewww.ibm.com/­products/­db2-event-storequasar.ai
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerdocs.datomic.comcloud.google.com/­datastore/­docswww.ibm.com/­docs/­en/­db2-event-storedoc.quasar.ai/­master
DeveloperDGraph LabsCognitectGoogleIBMquasardb
Initial release20172012200820172009
Current release1.0.6735, June 20232.03.14.1, January 2024
License infoCommercial or Open SourceOpen Source infoApache 2.0commercial infolimited edition freecommercialcommercial infofree developer edition availablecommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licenses
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoJava, ClojureC and C++C++
Server operating systemsBSD
Linux
OS X
Solaris
Windows
All OS with a Java VMhostedLinux infoLinux, macOS, Windows for the developer additionBSD
Linux
OS X
Windows
Data schemeschema-freeyesschema-freeyesschema-free
Typing infopredefined data types such as float or datenoyesyes, details hereyesyes infointeger and binary
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.nonononono
Secondary indexesnoyesyesnoyes infowith tags
SQL infoSupport of SQLnonoSQL-like query language (GQL)yes infothrough the embedded Spark runtimeSQL-like query language
APIs and other access methodsRESTful HTTP APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
HTTP API
Supported programming languagesGoClojure
Java
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Server-side scripts infoStored proceduresnoyes infoTransaction Functionsusing Google App Engineyesno
TriggersnoBy using transaction functionsCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesnonenone infoBut extensive use of caching in the application peersShardingShardingSharding infoconsistent hashing
Replication methods infoMethods for redundantly storing data on multiple nodesnonenone infoBut extensive use of caching in the application peersMulti-source replication using PaxosActive-active shard replicationSource-replica replication with selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflownowith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate 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 Consistency
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesNo - written data is immutableyes
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 storageyes infoby using LevelDB
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 developmentnoyesyes infoTransient mode
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-standardCryptographically strong user authentication and audit trail

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More resources
BadgerDatomicGoogle Cloud DatastoreIBM Db2 Event StoreQuasardb
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