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DBMS > Databricks vs. Datomic vs. GridGain vs. Microsoft Azure Synapse Analytics

System Properties Comparison Databricks vs. Datomic vs. GridGain vs. Microsoft Azure Synapse Analytics

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonDatomic  Xexclude from comparisonGridGain  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  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.Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityGridGain is an in-memory computing platform, built on Apache IgniteElastic, large scale data warehouse service leveraging the broad eco-system of SQL Server
Primary database modelDocument store
Relational DBMS
Relational DBMSKey-value store
Relational DBMS
Relational 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
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score20.56
Rank#31  Overall
#19  Relational DBMS
Websitewww.databricks.comwww.datomic.comwww.gridgain.comazure.microsoft.com/­services/­synapse-analytics
Technical documentationdocs.databricks.comdocs.datomic.comwww.gridgain.com/­docs/­index.htmldocs.microsoft.com/­azure/­synapse-analytics
DeveloperDatabricksCognitectGridGain Systems, Inc.Microsoft
Initial release2013201220072016
Current release1.0.6735, June 2023GridGain 8.5.1
License infoCommercial or Open Sourcecommercialcommercial infolimited edition freecommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureJava, C++, .NetC++
Server operating systemshostedAll OS with a Java VMLinux
OS X
Solaris
Windows
hosted
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesyes
Typing infopredefined data types such as float or dateyesyesyes
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.yesnoyesno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLwith Databricks SQLnoANSI-99 for query and DML statements, subset of DDLyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
RESTful HTTP APIHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
ADO.NET
JDBC
ODBC
Supported programming languagesPython
R
Scala
Clojure
Java
C#
C++
Java
PHP
Python
Ruby
Scala
C#
Java
PHP
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infoTransaction Functionsyes (compute grid and cache interceptors can be used instead)Transact SQL
TriggersBy using transaction functionsyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingSharding, horizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesnone infoBut extensive use of caching in the application peersyes (replicated cache)yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraints
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes inforecommended only for testing and developmentyes
User concepts infoAccess controlnoSecurity Hooks for custom implementationsyes
More information provided by the system vendor
DatabricksDatomicGridGainMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksDatomicGridGainMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse
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