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DBMS > Databricks vs. EJDB vs. Google Cloud Spanner vs. Microsoft Azure Table Storage

System Properties Comparison Databricks vs. EJDB vs. Google Cloud Spanner vs. Microsoft Azure Table Storage

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonEJDB  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonMicrosoft Azure Table Storage  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.Embeddable document-store database library with JSON representation of queries (in MongoDB style)A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.A Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelDocument store
Relational DBMS
Document storeRelational DBMSWide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score84.24
Rank#14  Overall
#2  Document stores
#9  Relational DBMS
Score0.13
Rank#331  Overall
#46  Document stores
Score2.69
Rank#101  Overall
#51  Relational DBMS
Score3.55
Rank#80  Overall
#6  Wide column stores
Websitewww.databricks.comgithub.com/­Softmotions/­ejdbcloud.google.com/­spannerazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationdocs.databricks.comgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mdcloud.google.com/­spanner/­docs
DeveloperDatabricksSoftmotionsGoogleMicrosoft
Initial release2013201220172012
License infoCommercial or Open SourcecommercialOpen Source infoGPLv2commercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC
Server operating systemshostedserver-lesshostedhosted
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesschema-free
Typing infopredefined data types such as float or dateyes infostring, integer, double, bool, date, object_idyesyes
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 indexesyesnoyesno
SQL infoSupport of SQLwith Databricks SQLnoyes infoQuery statements complying to ANSI 2011no
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
in-process shared librarygRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
RESTful HTTP API
Supported programming languagesPython
R
Scala
Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
Go
Java
JavaScript (Node.js)
Python
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesnonono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneMulti-source replication with 3 replicas for regional instances.yes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not needed, however similar functionality with collection joins possibleyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infoStrict serializable isolationoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/Write Lockingyesyes
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.nonono
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights based on private key authentication or shared access signatures
More information provided by the system vendor
DatabricksEJDBGoogle Cloud SpannerMicrosoft Azure Table Storage
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksEJDBGoogle Cloud SpannerMicrosoft Azure Table Storage
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