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DBMS > Databricks vs. Firebird vs. Hazelcast vs. Sqrrl

System Properties Comparison Databricks vs. Firebird vs. Hazelcast vs. Sqrrl

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonFirebird  Xexclude from comparisonHazelcast  Xexclude from comparisonSqrrl  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been 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.Firebird is an open source RDBMS forked from Borland's InterBaseA widely adopted in-memory data gridAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelDocument store
Relational DBMS
Relational DBMSKey-value storeDocument store
Graph DBMS
Key-value store
Wide column store
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score76.33
Rank#17  Overall
#3  Document stores
#11  Relational DBMS
Score21.06
Rank#31  Overall
#19  Relational DBMS
Score6.87
Rank#55  Overall
#6  Key-value stores
Websitewww.databricks.comwww.firebirdsql.orghazelcast.comsqrrl.com
Technical documentationdocs.databricks.comwww.firebirdsql.org/­en/­reference-manualshazelcast.org/­imdg/­docs
DeveloperDatabricksFirebird FoundationHazelcastAmazon infooriginally Sqrrl Data, Inc.
Initial release20132000 infoAs fork of Borland's InterBase20082012
Current release5.0.0, January 20245.3.6, November 2023
License infoCommercial or Open SourcecommercialOpen Source infoInitial Developer's Public LicenseOpen Source infoApache Version 2; commercial licenses availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC and C++JavaJava
Server operating systemshostedAIX
FreeBSD
HP-UX
Linux
OS X
server-less infoFirebird Embedded Server
Solaris
Unix
Windows
All OS with a Java VMLinux
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeschema-free
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.yesyes infothe object must implement a serialization strategy
Secondary indexesyesyesyesyes
SQL infoSupport of SQLwith Databricks SQLyesSQL-like query languageno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
C/C++ API
JDBC infoJaybird
ODBC
OLE DB
JCache
JPA
Memcached protocol
RESTful HTTP API
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesPython
R
Scala
C
C#
C++
Delphi
Java
JavaScript infoNode.js
Lua
Perl
PHP
Python
Ruby
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresuser defined functions and aggregatesPSQLyes infoEvent Listeners, Executor Servicesno
Triggersyesyes infoEventsno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationyes infoReplicated Mapselectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDone or two-phase-commit; repeatable reads; read commitedAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyes infoFeatures a multi-generational MVCC architecture, readers do not block writersyesyes
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.noyes
User concepts infoAccess controlUsers with fine-grained authorization conceptRole-based access controlCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)
More information provided by the system vendor
DatabricksFirebirdHazelcastSqrrl
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksFirebirdHazelcastSqrrl
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