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

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

Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisondBASE  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionConverged and high performance database for device data, events, time series, document and graphdBase 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 modelDocument store
Graph DBMS
Time Series DBMS
Relational DBMSKey-value store
Wide column store
Event Store
Time Series DBMS
Relational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.08
Rank#347  Overall
#47  Document stores
#34  Graph DBMS
#31  Time Series DBMS
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
Websitebangdb.comwww.dbase.comcloud.google.com/­bigtablewww.ibm.com/­products/­db2-event-storespark.apache.org/­sql
Technical documentationdocs.bangdb.comwww.dbase.com/­support/­knowledgebasecloud.google.com/­bigtable/­docswww.ibm.com/­docs/­en/­db2-event-storespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperSachin Sinha, BangDBAsthon TateGoogleIBMApache Software Foundation
Initial release20121979201520172014
Current releaseBangDB 2.0, October 2021dBASE 2019, 20192.03.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoBSD 3commercialcommercialcommercial 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

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Implementation languageC, C++C and C++Scala
Server operating systemsLinuxDOS 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 dateyes: string, long, double, int, geospatial, stream, eventsyesnoyesyes
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 indexesyes infosecondary, composite, nested, reverse, geospatialyesnonono
SQL infoSupport of SQLSQL like support with command line toolnonoyes infothrough the embedded Spark runtimeSQL-like DML and DDL statements
APIs and other access methodsProprietary protocol
RESTful HTTP API
none 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 languagesC
C#
C++
Java
Python
dBase 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
Triggersyes, Notifications (with Streaming only)nononono
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmnoneShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)noneInternal 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 systemTunable consistency, set CAP knob accordinglyImmediate 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 dataACIDno infonot for dBase internal data, but IDE does support transactions when accessing external DBMSAtomic single-row operationsnono
Concurrency infoSupport for concurrent manipulation of datayes, optimistic concurrency controlyesyesNo - written data is immutableyes
Durability infoSupport for making data persistentyes, implements WAL (Write ahead log) as wellyesyesYes - 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, run db with in-memory only modenoyesno
User concepts infoAccess controlyes (enterprise version only)Access 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
BangdbdBASEGoogle Cloud BigtableIBM Db2 Event StoreSpark SQL
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