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DBMS > Databricks vs. Dgraph vs. EsgynDB vs. Google Cloud Bigtable vs. GridGain

System Properties Comparison Databricks vs. Dgraph vs. EsgynDB vs. Google Cloud Bigtable vs. GridGain

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonDgraph  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonGridGain  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.Distributed and scalable native Graph DBMSEnterprise-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.GridGain is an in-memory computing platform, built on Apache Ignite
Primary database modelDocument store
Relational DBMS
Graph DBMSRelational DBMSKey-value store
Wide column store
Key-value 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
Score1.45
Rank#156  Overall
#15  Graph DBMS
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Websitewww.databricks.comdgraph.iowww.esgyn.cncloud.google.com/­bigtablewww.gridgain.com
Technical documentationdocs.databricks.comdgraph.io/­docscloud.google.com/­bigtable/­docswww.gridgain.com/­docs/­index.html
DeveloperDatabricksDgraph Labs, Inc.EsgynGoogleGridGain Systems, Inc.
Initial release20132016201520152007
Current releaseGridGain 8.5.1
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialcommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC++, JavaJava, C++, .Net
Server operating systemshostedLinux
OS X
Windows
LinuxhostedLinux
OS X
Solaris
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes
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.yesnononoyes
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLwith Databricks SQLnoyesnoANSI-99 for query and DML statements, subset of DDL
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
GraphQL query language
gRPC (using protocol buffers) API
HTTP API
ADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Supported programming languagesPython
R
Scala
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
All languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
C#
C++
Java
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoJava Stored Proceduresnoyes (compute grid and cache interceptors can be used instead)
Triggersnononoyes (cache interceptors and events)
Partitioning methods infoMethods for storing different data on different nodesyesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesSynchronous replication via RaftMulti-source replication between multi datacentersInternal replication in Colossus, and regional replication between two clusters in different zonesyes (replicated cache)
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesyes (compute grid and hadoop accelerator)
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDAtomic single-row operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes
User concepts infoAccess controlno infoPlanned for future releasesfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Security Hooks for custom implementations
More information provided by the system vendor
DatabricksDgraphEsgynDBGoogle Cloud BigtableGridGain
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksDgraphEsgynDBGoogle Cloud BigtableGridGain
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