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DBMS > Databricks vs. EsgynDB vs. Faircom EDGE vs. Google Cloud Bigtable

System Properties Comparison Databricks vs. EsgynDB vs. Faircom EDGE vs. Google Cloud Bigtable

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonEsgynDB  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonGoogle Cloud Bigtable  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 environmentsGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.
Primary database modelDocument store
Relational DBMS
Relational DBMSKey-value store
Relational DBMS
Key-value store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score0.09
Rank#362  Overall
#53  Key-value stores
#155  Relational DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Websitewww.databricks.comwww.esgyn.cnwww.faircom.com/­products/­faircom-edgecloud.google.com/­bigtable
Technical documentationdocs.databricks.comdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlcloud.google.com/­bigtable/­docs
DeveloperDatabricksEsgynFairCom CorporationGoogle
Initial release2013201519792015
Current releaseV3, October 2020
License infoCommercial or Open Sourcecommercialcommercialcommercial infoRestricted, free version availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaANSI C, C++
Server operating systemshostedLinuxAndroid
Linux infoARM, x86
Raspbian
Windows
hosted
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 Typesno
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 indexesyesyesyesno
SQL infoSupport of SQLwith Databricks SQLyesyes infoANSI SQL queriesno
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
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Supported programming languagesPython
R
Scala
All languages supporting JDBC/ODBC/ADO.NetC
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C#
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesJava Stored Proceduresyes info.Net, JavaScript, C/C++no
Triggersnoyesno
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 logsInternal replication in Colossus, and regional replication between two clusters in different zones
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 (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integrityyesyes infowhen using SQLno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDAtomic single-row operations
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.nonoyesno
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.Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)
More information provided by the system vendor
DatabricksEsgynDBFaircom EDGE infoformerly c-treeEDGEGoogle Cloud Bigtable
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksEsgynDBFaircom EDGE infoformerly c-treeEDGEGoogle Cloud Bigtable
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