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

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

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Editorial information provided by DB-Engines
NameDatabricks  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.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
Key-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
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score7.03
Rank#54  Overall
#5  Key-value stores
Score0.27
Rank#309  Overall
#2  Event Stores
#28  Time Series DBMS
Score44.87
Rank#22  Overall
#15  Relational DBMS
Websitewww.databricks.cometcd.io
github.com/­etcd-io/­etcd
www.ibm.com/­products/­db2-event-storewww.teradata.com
Technical documentationdocs.databricks.cometcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
www.ibm.com/­docs/­en/­db2-event-storedocs.teradata.com
DeveloperDatabricksIBMTeradata
Initial release201320171984
Current release3.4, August 20192.0Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercial infofree developer edition availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC and C++
Server operating systemshostedFreeBSD
Linux
Windows infoexperimental
Linux infoLinux, macOS, Windows for the developer additionhosted
Linux
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesyes
Typing infopredefined data types such as float or datenoyesyes
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 indexesyesnonoyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLwith Databricks SQLnoyes infothrough the embedded Spark runtimeyes infoSQL 2016 + extensions
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
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
.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 aggregatesnoyesyes infoUDFs, stored procedures, table functions in parallel
Triggersyes, watching key changesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesyesUsing 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 methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesNo - written data is immutableyes
Durability infoSupport for making data persistentyesyesYes - 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 controlnofine grained access rights according to SQL-standardfine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksetcdIBM Db2 Event StoreTeradata
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksetcdIBM Db2 Event StoreTeradata
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