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DBMS > Badger vs. dBASE vs. Google Cloud Bigtable vs. IBM Db2 Event Store vs. Spark SQL

System Properties Comparison Badger vs. dBASE vs. Google Cloud Bigtable vs. IBM Db2 Event Store vs. Spark SQL

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisondBASE  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.dBase was one of the first databases with a development environment on PC's. Its latest version dBase V is still sold as dBase classic, which needs a DOS Emulation. The up-to-date product is dBase plus.Google'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 casesSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value storeRelational DBMSKey-value store
Wide column store
Event Store
Time Series DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#331  Overall
#49  Key-value stores
Score10.34
Rank#44  Overall
#28  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
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitegithub.com/­dgraph-io/­badgerwww.dbase.comcloud.google.com/­bigtablewww.ibm.com/­products/­db2-event-storespark.apache.org/­sql
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerwww.dbase.com/­support/­knowledgebasecloud.google.com/­bigtable/­docswww.ibm.com/­docs/­en/­db2-event-storespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDGraph LabsAsthon TateGoogleIBMApache Software Foundation
Initial release20171979201520172014
Current releasedBASE 2019, 20192.03.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialcommercial infofree developer edition availableOpen Source infoApache 2.0
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 languageGoC and C++Scala
Server operating systemsBSD
Linux
OS X
Solaris
Windows
DOS infodBase Classic
Windows infodBase Pro
hostedLinux infoLinux, macOS, Windows for the developer additionLinux
OS X
Windows
Data schemeschema-freeyesschema-freeyesyes
Typing infopredefined data types such as float or datenoyesnoyesyes
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 indexesnoyesnonono
SQL infoSupport of SQLnononoyes infothrough the embedded Spark runtimeSQL-like DML and DDL statements
APIs and other access methodsnone infoThe IDE can access other DBMS or ODBC-sources.gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Supported programming languagesGodBase proprietary IDEC#
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
Java
Python
R
Scala
Server-side scripts infoStored proceduresnono infoThe IDE can access stored procedures in other database systems.noyesno
Triggersnonononono
Partitioning methods infoMethods for storing different data on different nodesnonenoneShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnonenoneInternal replication in Colossus, and regional replication between two clusters in different zonesActive-active shard replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistency
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infonot for dBase internal data, but IDE does support transactions when accessing external DBMSAtomic single-row operationsnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesNo - written data is immutableyes
Durability infoSupport for making data persistentyesyesyesYes - 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.nonoyesno
User concepts infoAccess controlnoAccess rights for users and rolesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardno

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More resources
BadgerdBASEGoogle Cloud BigtableIBM Db2 Event StoreSpark SQL
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