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DBMS > Databricks vs. EsgynDB vs. Google Cloud Bigtable vs. Kdb vs. LeanXcale

System Properties Comparison Databricks vs. EsgynDB vs. Google Cloud Bigtable vs. Kdb vs. LeanXcale

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonKdb  Xexclude from comparisonLeanXcale  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.Enterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.High performance Time Series DBMSA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities
Primary database modelDocument store
Relational DBMS
Relational DBMSKey-value store
Wide column store
Time Series DBMS
Vector DBMS
Key-value store
Relational DBMS
Secondary database modelsRelational 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
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score7.55
Rank#53  Overall
#3  Time Series DBMS
#1  Vector DBMS
Score0.29
Rank#291  Overall
#41  Key-value stores
#132  Relational DBMS
Websitewww.databricks.comwww.esgyn.cncloud.google.com/­bigtablekx.comwww.leanxcale.com
Technical documentationdocs.databricks.comcloud.google.com/­bigtable/­docscode.kx.com
DeveloperDatabricksEsgynGoogleKx Systems, a division of First Derivatives plcLeanXcale
Initial release2013201520152000 infokdb was released 2000, kdb+ in 20032015
Current release3.6, May 2018
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercial infofree 32-bit versioncommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, Javaq
Server operating systemshostedLinuxhostedLinux
OS X
Solaris
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyes
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 indexesyesyesnoyes infotable attribute 'grouped'
SQL infoSupport of SQLwith Databricks SQLyesnoSQL-like query language (q)yes infothrough Apache Derby
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
Supported programming languagesPython
R
Scala
All languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
C
Java
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesJava Stored Proceduresnouser defined functions
Triggersnonoyes infowith views
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication between multi datacentersInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesno infosimilar paradigm used for internal processingno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDAtomic single-row operationsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)rights management via user accounts
More information provided by the system vendor
DatabricksEsgynDBGoogle Cloud BigtableKdbLeanXcale
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
Integrated columnar database & programming system for streaming, real time and historical...
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Competitive advantagesprovides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more
Typical application scenariostick database streaming sensor data massive intelligence applications oil and gas...
» more
Key customersGoldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
Market metricskdb+ performance and reliability proven by our customers in critical infrastructure...
» more
Licensing and pricing modelsupon request
» more

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More resources
DatabricksEsgynDBGoogle Cloud BigtableKdbLeanXcale
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