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DBMS > Databricks vs. eXtremeDB vs. GeoSpock vs. LeanXcale

System Properties Comparison Databricks vs. eXtremeDB vs. GeoSpock vs. LeanXcale

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisoneXtremeDB  Xexclude from comparisonGeoSpock  Xexclude from comparisonLeanXcale  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.
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.Natively in-memory DBMS with options for persistency, high-availability and clusteringSpatial and temporal data processing engine for extreme data scaleA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities
Primary database modelDocument store
Relational DBMS
Relational DBMS
Time Series DBMS
Relational DBMSKey-value store
Relational DBMS
Secondary database modelsTime 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
Score0.80
Rank#214  Overall
#99  Relational DBMS
#18  Time Series DBMS
Score0.36
Rank#280  Overall
#40  Key-value stores
#129  Relational DBMS
Websitewww.databricks.comwww.mcobject.comgeospock.comwww.leanxcale.com
Technical documentationdocs.databricks.comwww.mcobject.com/­docs/­extremedb.htm
DeveloperDatabricksMcObjectGeoSpockLeanXcale
Initial release201320012015
Current release8.2, 20212.0, September 2019
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and C++Java, Javascript
Server operating systemshostedAIX
HP-UX
Linux
macOS
Solaris
Windows
hosted
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesyes
Typing infopredefined data types such as float or dateyesyes
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.yesno infosupport of XML interfaces availableno
Secondary indexesyesyestemporal, categorical
SQL infoSupport of SQLwith Databricks SQLyes infowith the option: eXtremeSQLANSI SQL for query only (using Presto)yes infothrough Apache Derby
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
JDBCJDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
Supported programming languagesPython
R
Scala
.Net
C
C#
C++
Java
Lua
Python
Scala
C
Java
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesno
Triggersyes infoby defining eventsno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning / shardingAutomatic sharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesActive Replication Fabricâ„¢ for IoT
Multi-source replication infoby means of eXtremeDB Cluster option
Source-replica replication infoby means of eXtremeDB High Availability option
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoOptimistic (MVCC) and pessimistic (locking) strategies availableyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes
User concepts infoAccess controlAccess rights for users can be defined per table
More information provided by the system vendor
DatabrickseXtremeDBGeoSpockLeanXcale
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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eXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
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Competitive advantageseXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
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Typical application scenariosIoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
» more
Key customersSchneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more
Market metricsWith hundreds of customers and over 30 million devices/applications using the product...
» more
Licensing and pricing modelsFor server use cases, there is a simple per-server license irrespective of the number...
» more

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More resources
DatabrickseXtremeDBGeoSpockLeanXcale
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