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DBMS > Databricks vs. dBASE vs. etcd vs. IBM Db2 Event Store vs. Teradata

System Properties Comparison Databricks vs. dBASE vs. etcd vs. IBM Db2 Event Store vs. Teradata

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisondBASE  Xexclude from comparisonetcd  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.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.A distributed reliable key-value storeDistributed Event Store optimized for Internet of Things use casesA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelDocument store
Relational DBMS
Relational DBMSKey-value storeEvent Store
Time Series DBMS
Relational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score10.34
Rank#44  Overall
#28  Relational DBMS
Score7.25
Rank#54  Overall
#5  Key-value stores
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Score45.33
Rank#21  Overall
#15  Relational DBMS
Websitewww.databricks.comwww.dbase.cometcd.io
github.com/­etcd-io/­etcd
www.ibm.com/­products/­db2-event-storewww.teradata.com
Technical documentationdocs.databricks.comwww.dbase.com/­support/­knowledgebaseetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
www.ibm.com/­docs/­en/­db2-event-storedocs.teradata.com
DeveloperDatabricksAsthon TateIBMTeradata
Initial release2013197920171984
Current releasedBASE 2019, 20193.4, August 20192.0Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2.0commercial infofree developer edition availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC and C++
Server operating systemshostedDOS infodBase Classic
Windows infodBase Pro
FreeBSD
Linux
Windows infoexperimental
Linux infoLinux, macOS, Windows for the developer additionhosted
Linux
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyesyes
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.yesnonoyes
Secondary indexesyesyesnonoyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLwith Databricks SQLnonoyes infothrough the embedded Spark runtimeyes infoSQL 2016 + extensions
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
none infoThe IDE can access other DBMS or ODBC-sources.gRPC
JSON over HTTP
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languagesPython
R
Scala
dBase proprietary IDE.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesno infoThe IDE can access stored procedures in other database systems.noyesyes infoUDFs, stored procedures, table functions in parallel
Triggersnoyes, watching key changesnoyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Active-active shard replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonoyes
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 DBMSnonoACID
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.nonoyesyes
User concepts infoAccess controlAccess rights for users and rolesnofine grained access rights according to SQL-standardfine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksdBASEetcdIBM Db2 Event StoreTeradata
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksdBASEetcdIBM Db2 Event StoreTeradata
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