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DBMS > Databricks vs. EsgynDB vs. Google Cloud Bigtable vs. Hive

System Properties Comparison Databricks vs. EsgynDB vs. Google Cloud Bigtable vs. Hive

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHive  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 TrafodionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.data warehouse software for querying and managing large distributed datasets, built on Hadoop
Primary database modelDocument store
Relational DBMS
Relational DBMSKey-value store
Wide column store
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
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score61.17
Rank#18  Overall
#12  Relational DBMS
Websitewww.databricks.comwww.esgyn.cncloud.google.com/­bigtablehive.apache.org
Technical documentationdocs.databricks.comcloud.google.com/­bigtable/­docscwiki.apache.org/­confluence/­display/­Hive/­Home
DeveloperDatabricksEsgynGoogleApache Software Foundation infoinitially developed by Facebook
Initial release2013201520152012
Current release3.1.3, April 2022
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaJava
Server operating systemshostedLinuxhostedAll OS with a Java VM
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeyes
Typing infopredefined data types such as float or dateyesnoyes
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.yesnono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLwith Databricks SQLyesnoSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Thrift
Supported programming languagesPython
R
Scala
All languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
C++
Java
PHP
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesJava Stored Proceduresnoyes infouser defined functions and integration of map-reduce
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication between multi datacentersInternal replication in Colossus, and regional replication between two clusters in different zonesselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesyes infoquery execution via MapReduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistency
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDAtomic single-row operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.nonono
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and roles
More information provided by the system vendor
DatabricksEsgynDBGoogle Cloud BigtableHive
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksEsgynDBGoogle Cloud BigtableHive
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