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DBMS > Databricks vs. HBase vs. Microsoft Azure Synapse Analytics vs. NSDb vs. WakandaDB

System Properties Comparison Databricks vs. HBase vs. Microsoft Azure Synapse Analytics vs. NSDb vs. WakandaDB

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonHBase  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonNSDb  Xexclude from comparisonWakandaDB  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.Wide-column store based on Apache Hadoop and on concepts of BigTableElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelDocument store
Relational DBMS
Wide column storeRelational DBMSTime Series DBMSObject oriented 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
Score30.50
Rank#26  Overall
#2  Wide column stores
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score0.03
Rank#364  Overall
#17  Object oriented DBMS
Websitewww.databricks.comhbase.apache.orgazure.microsoft.com/­services/­synapse-analyticsnsdb.iowakanda.github.io
Technical documentationdocs.databricks.comhbase.apache.org/­book.htmldocs.microsoft.com/­azure/­synapse-analyticsnsdb.io/­Architecturewakanda.github.io/­doc
DeveloperDatabricksApache Software Foundation infoApache top-level project, originally developed by PowersetMicrosoftWakanda SAS
Initial release20132008201620172012
Current release2.3.4, January 20212.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2commercialOpen Source infoApache Version 2.0Open Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++Java, ScalaC++, JavaScript
Server operating systemshostedLinux
Unix
Windows infousing Cygwin
hostedLinux
macOS
Linux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-free, schema definition possibleyesyes
Typing infopredefined data types such as float or dateoptions to bring your own types, AVROyesyes: int, bigint, decimal, stringyes
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.yesnononono
Secondary indexesyesnoyesall fields are automatically indexed
SQL infoSupport of SQLwith Databricks SQLnoyesSQL-like query languageno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP API
Thrift
ADO.NET
JDBC
ODBC
gRPC
HTTP REST
WebSocket
RESTful HTTP API
Supported programming languagesPython
R
Scala
C
C#
C++
Groovy
Java
PHP
Python
Scala
C#
Java
PHP
Java
Scala
JavaScript
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infoCoprocessors in JavaTransact SQLnoyes
Triggersyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding, horizontal partitioningShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
yesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDSingle row ACID (across millions of columns)ACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesUsing Apache Luceneyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACyesyes
More information provided by the system vendor
DatabricksHBaseMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseNSDbWakandaDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksHBaseMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseNSDbWakandaDB
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