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

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

Editorial information provided by DB-Engines
NameAgensGraph  Xexclude from comparisonDatabricks  Xexclude from comparisonDgraph  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparison
DescriptionMulti-model database supporting relational and graph data models and built upon PostgreSQLThe 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.
Primary database modelGraph DBMS
Relational DBMS
Document store
Relational DBMS
Graph DBMSRelational DBMSKey-value store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.20
Rank#321  Overall
#27  Graph DBMS
#143  Relational DBMS
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
Websitebitnine.net/­agensgraphwww.databricks.comdgraph.iowww.esgyn.cncloud.google.com/­bigtable
Technical documentationbitnine.net/­documentationdocs.databricks.comdgraph.io/­docscloud.google.com/­bigtable/­docs
DeveloperBitnine Global Inc.DatabricksDgraph Labs, Inc.EsgynGoogle
Initial release20162013201620152015
Current release2.1, December 2018
License infoCommercial or Open SourceOpen Source infoApache License 2.0commercialOpen Source infoApache 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesnonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCGoC++, Java
Server operating systemsLinux
OS X
Windows
hostedLinux
OS X
Windows
Linuxhosted
Data schemedepending on used data modelFlexible Schema (defined schema, partial schema, schema free)schema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesyesno
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.noyesnonono
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLyeswith Databricks SQLnoyesno
APIs and other access methodsCypher Query Language
JDBC
JDBC
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)
Supported programming languagesC
Java
JavaScript
Python
Python
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
Server-side scripts infoStored proceduresyesuser defined functions and aggregatesnoJava Stored Proceduresno
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesno, but can be realized using table inheritanceyesShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyesSynchronous replication via RaftMulti-source replication between multi datacentersInternal replication in Colossus, and regional replication between two clusters in different zones
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integrityyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACIDAtomic single-row operations
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.nononono
User concepts infoAccess controlfine grained access rights according to SQL-standardno 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)
More information provided by the system vendor
AgensGraphDatabricksDgraphEsgynDBGoogle Cloud Bigtable
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
AgensGraphDatabricksDgraphEsgynDBGoogle Cloud Bigtable
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