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DBMS > Databricks vs. etcd vs. HBase vs. VoltDB

System Properties Comparison Databricks vs. etcd vs. HBase vs. VoltDB

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonetcd  Xexclude from comparisonHBase  Xexclude from comparisonVoltDB  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 storeWide-column store based on Apache Hadoop and on concepts of BigTableDistributed In-Memory NewSQL RDBMS infoUsed for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory
Primary database modelDocument store
Relational DBMS
Key-value storeWide column storeRelational 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
Score7.25
Rank#54  Overall
#5  Key-value stores
Score30.50
Rank#26  Overall
#2  Wide column stores
Score1.44
Rank#158  Overall
#73  Relational DBMS
Websitewww.databricks.cometcd.io
github.com/­etcd-io/­etcd
hbase.apache.orgwww.voltdb.com
Technical documentationdocs.databricks.cometcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
hbase.apache.org/­book.htmldocs.voltdb.com
DeveloperDatabricksApache Software Foundation infoApache top-level project, originally developed by PowersetVoltDB Inc.
Initial release201320082010
Current release3.4, August 20192.3.4, January 202111.3, April 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoApache version 2Open Source infoAGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoJavaJava, C++
Server operating systemshostedFreeBSD
Linux
Windows infoexperimental
Linux
Unix
Windows infousing Cygwin
Linux
OS X infofor development
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-free, schema definition possibleyes
Typing infopredefined data types such as float or datenooptions to bring your own types, AVROyes
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.yesnono
Secondary indexesyesnonoyes
SQL infoSupport of SQLwith Databricks SQLnonoyes infoonly a subset of SQL 99
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
gRPC
JSON over HTTP
Java API
RESTful HTTP API
Thrift
Java API
JDBC
RESTful HTTP/JSON API
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++
Groovy
Java
PHP
Python
Scala
C#
C++
Erlang infonot officially supported
Go
Java
JavaScript infoNode.js
PHP
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoyes infoCoprocessors in JavaJava
Triggersyes, watching key changesyesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Multi-source replication
Source-replica replication
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency
Foreign keys infoReferential integritynonono infoFOREIGN KEY constraints are not supported
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoSingle row ACID (across millions of columns)ACID infoTransactions are executed single-threaded within stored procedures
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoData access is serialized by the server
Durability infoSupport for making data persistentyesyesyesyes infoSnapshots and command logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlnoAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACUsers and roles with access to stored procedures
More information provided by the system vendor
DatabricksetcdHBaseVoltDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksetcdHBaseVoltDB
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