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DBMS > Databricks vs. EsgynDB vs. Faircom EDGE vs. Hazelcast

System Properties Comparison Databricks vs. EsgynDB vs. Faircom EDGE vs. Hazelcast

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonEsgynDB  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonHazelcast  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.Enterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsA widely adopted in-memory data grid
Primary database modelDocument store
Relational DBMS
Relational DBMSKey-value store
Relational DBMS
Key-value store
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score84.24
Rank#14  Overall
#2  Document stores
#9  Relational DBMS
Score0.15
Rank#325  Overall
#144  Relational DBMS
Score0.02
Rank#370  Overall
#55  Key-value stores
#157  Relational DBMS
Score5.72
Rank#59  Overall
#6  Key-value stores
Websitewww.databricks.comwww.esgyn.cnwww.faircom.com/­products/­faircom-edgehazelcast.com
Technical documentationdocs.databricks.comdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlhazelcast.org/­imdg/­docs
DeveloperDatabricksEsgynFairCom CorporationHazelcast
Initial release2013201519792008
Current releaseV3, October 20205.3.6, November 2023
License infoCommercial or Open Sourcecommercialcommercialcommercial infoRestricted, free version availableOpen Source infoApache Version 2; commercial licenses available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaANSI C, C++Java
Server operating systemshostedLinuxAndroid
Linux infoARM, x86
Raspbian
Windows
All OS with a Java VM
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesFlexible Schema (defined schema, partial schema, schema free)schema-free
Typing infopredefined data types such as float or dateyesyes, ANSI Standard SQL Typesyes
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.yesnoyesyes infothe object must implement a serialization strategy
Secondary indexesyesyesyesyes
SQL infoSupport of SQLwith Databricks SQLyesyes infoANSI SQL queriesSQL-like query language
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
JCache
JPA
Memcached protocol
RESTful HTTP API
Supported programming languagesPython
R
Scala
All languages supporting JDBC/ODBC/ADO.NetC
C#
C++
Java
JavaScript
PHP
Python
VB.Net
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesJava Stored Proceduresyes info.Net, JavaScript, C/C++yes infoEvent Listeners, Executor Services
Triggersnoyesyes infoEvents
Partitioning methods infoMethods for storing different data on different nodesShardingFile partitioning infoCustomizable business rules for partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication between multi datacentersyes infoSynchronous and asynchronous realtime replication based on transaction logsyes infoReplicated Map
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Tunable Consistency
Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus Algorithm
Foreign keys infoReferential integrityyesyes infowhen using SQLno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDone or two-phase-commit; repeatable reads; read commited
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoacross SQL and NoSQLyes
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.nonoyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Role-based access control
More information provided by the system vendor
DatabricksEsgynDBFaircom EDGE infoformerly c-treeEDGEHazelcast
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksEsgynDBFaircom EDGE infoformerly c-treeEDGEHazelcast
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