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DBMS > Databricks vs. GBase vs. Hypertable vs. NSDb

System Properties Comparison Databricks vs. GBase vs. Hypertable vs. NSDb

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGBase  Xexclude from comparisonHypertable  Xexclude from comparisonNSDb  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed 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.Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.An open source BigTable implementation based on distributed file systems such as HadoopScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes
Primary database modelDocument store
Relational DBMS
Relational DBMSWide column storeTime 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
Score1.05
Rank#186  Overall
#86  Relational DBMS
Score0.08
Rank#369  Overall
#40  Time Series DBMS
Websitewww.databricks.comwww.gbase.cnnsdb.io
Technical documentationdocs.databricks.comnsdb.io/­Architecture
DeveloperDatabricksGeneral Data Technology Co., Ltd.Hypertable Inc.
Initial release2013200420092017
Current releaseGBase 8a, GBase 8s, GBase 8c0.9.8.11, March 2016
License infoCommercial or Open SourcecommercialcommercialOpen Source infoGNU version 3. Commercial license availableOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, Java, PythonC++Java, Scala
Server operating systemshostedLinuxLinux
OS X
Windows infoan inofficial Windows port is available
Linux
macOS
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-free
Typing infopredefined data types such as float or dateyesnoyes: int, bigint, decimal, string
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.yesyesno
Secondary indexesyesyesrestricted infoonly exact value or prefix value scansall fields are automatically indexed
SQL infoSupport of SQLwith Databricks SQLStandard with numerous extensionsnoSQL-like query language
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
C API
JDBC
ODBC
C++ API
Thrift
gRPC
HTTP REST
WebSocket
Supported programming languagesPython
R
Scala
C#C++
Java
Perl
PHP
Python
Ruby
Java
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesuser defined functionsnono
Triggersyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by range, list and hash) and vertical partitioningShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesselectable replication factor on file system level
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesUsing Apache Lucene
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlyesno
More information provided by the system vendor
DatabricksGBaseHypertableNSDb
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksGBaseHypertableNSDb
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