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DBMS > Databricks vs. FatDB vs. Ignite

System Properties Comparison Databricks vs. FatDB vs. Ignite

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonFatDB  Xexclude from comparisonIgnite  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the 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.A .NET NoSQL DBMS that can integrate with and extend SQL Server.Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.
Primary database modelDocument store
Relational DBMS
Document store
Key-value store
Key-value store
Relational 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
Score3.11
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Websitewww.databricks.comignite.apache.org
Technical documentationdocs.databricks.comapacheignite.readme.io/­docs
DeveloperDatabricksFatCloudApache Software Foundation
Initial release201320122015
Current releaseApache Ignite 2.6
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC#C++, Java, .Net
Server operating systemshostedWindowsLinux
OS X
Solaris
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyes
Typing infopredefined data types such as float or dateyesyes
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.yesyes
Secondary indexesyesyesyes
SQL infoSupport of SQLwith Databricks SQLno infoVia inetgration in SQL ServerANSI-99 for query and DML statements, subset of DDL
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Supported programming languagesPython
R
Scala
C#C#
C++
Java
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infovia applicationsyes (compute grid and cache interceptors can be used instead)
Triggersyes infovia applicationsyes (cache interceptors and events)
Partitioning methods infoMethods for storing different data on different nodesShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factoryes (replicated cache)
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes (compute grid and hadoop accelerator)
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlno infoCan implement custom security layer via applicationsSecurity Hooks for custom implementations
More information provided by the system vendor
DatabricksFatDBIgnite
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksFatDBIgnite
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