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DBMS > atoti vs. Databricks vs. etcd vs. EXASOL

System Properties Comparison atoti vs. Databricks vs. etcd vs. EXASOL

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Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonDatabricks  Xexclude from comparisonetcd  Xexclude from comparisonEXASOL  Xexclude from comparison
DescriptionAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.The 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 storeHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.
Primary database modelObject oriented DBMSDocument store
Relational DBMS
Key-value storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.61
Rank#243  Overall
#11  Object oriented DBMS
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score7.03
Rank#54  Overall
#5  Key-value stores
Score1.76
Rank#139  Overall
#62  Relational DBMS
Websiteatoti.iowww.databricks.cometcd.io
github.com/­etcd-io/­etcd
www.exasol.com
Technical documentationdocs.atoti.iodocs.databricks.cometcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
www.exasol.com/­resources
DeveloperActiveViamDatabricksExasol
Initial release20132000
Current release3.4, August 2019
License infoCommercial or Open Sourcecommercial infofree versions availablecommercialOpen Source infoApache Version 2.0commercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGo
Server operating systemshostedFreeBSD
Linux
Windows infoexperimental
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyes
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.yesnono
Secondary indexesyesnoyes
SQL infoSupport of SQLMultidimensional Expressions (MDX)with Databricks SQLnoyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
gRPC
JSON over HTTP
.Net
JDBC
ODBC
WebSocket
Supported programming languagesPython
R
Scala
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
Java
Lua
Python
R
Server-side scripts infoStored proceduresPythonuser defined functions and aggregatesnouser defined functions
Triggersyes, watching key changesyes
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infoHadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyes
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.yesnonoyes
User concepts infoAccess controlnoAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
atotiDatabricksetcdEXASOL
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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atotiDatabricksetcdEXASOL
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