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DBMS > Databricks vs. etcd vs. Hazelcast

System Properties Comparison Databricks vs. etcd vs. Hazelcast

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonetcd  Xexclude from comparisonHazelcast  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 storeA widely adopted in-memory data grid
Primary database modelDocument store
Relational DBMS
Key-value storeKey-value store
Secondary database modelsDocument store infoJSON support with IMDG 3.12
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
Score5.46
Rank#61  Overall
#7  Key-value stores
Websitewww.databricks.cometcd.io
github.com/­etcd-io/­etcd
hazelcast.com
Technical documentationdocs.databricks.cometcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
hazelcast.org/­imdg/­docs
DeveloperDatabricksHazelcast
Initial release20132008
Current release3.4, August 20195.3.6, November 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoApache Version 2; commercial licenses available
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoJava
Server operating systemshostedFreeBSD
Linux
Windows infoexperimental
All OS with a Java VM
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-free
Typing infopredefined data types such as float or datenoyes
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.yesnoyes infothe object must implement a serialization strategy
Secondary indexesyesnoyes
SQL infoSupport of SQLwith Databricks SQLnoSQL-like query language
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
gRPC
JSON over HTTP
JCache
JPA
Memcached protocol
RESTful HTTP 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
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoyes infoEvent Listeners, Executor Services
Triggersyes, watching key changesyes infoEvents
Partitioning methods infoMethods for storing different data on different nodesSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.yes infoReplicated Map
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus Algorithm
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoone or two-phase-commit; repeatable reads; read commited
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlnoRole-based access control
More information provided by the system vendor
DatabricksetcdHazelcast
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksetcdHazelcast
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