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DBMS > Databend vs. Dgraph vs. EsgynDB vs. Google Cloud Bigtable vs. Spark SQL

System Properties Comparison Databend vs. Dgraph vs. EsgynDB vs. Google Cloud Bigtable vs. Spark SQL

Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonDgraph  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityDistributed 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.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSGraph DBMSRelational DBMSKey-value store
Wide column store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.30
Rank#287  Overall
#130  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
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitegithub.com/­datafuselabs/­databend
www.databend.com
dgraph.iowww.esgyn.cncloud.google.com/­bigtablespark.apache.org/­sql
Technical documentationdocs.databend.comdgraph.io/­docscloud.google.com/­bigtable/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDatabend LabsDgraph Labs, Inc.EsgynGoogleApache Software Foundation
Initial release20212016201520152014
Current release1.0.59, April 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0commercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageRustGoC++, JavaScala
Server operating systemshosted
Linux
macOS
Linux
OS X
Windows
LinuxhostedLinux
OS X
Windows
Data schemeyesschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesnoyes
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.nonononono
Secondary indexesnoyesyesnono
SQL infoSupport of SQLyesnoyesnoSQL-like DML and DDL statements
APIs and other access methodsCLI Client
JDBC
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)
JDBC
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
All languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnonoJava Stored Proceduresnono
Triggersnonononono
Partitioning methods infoMethods for storing different data on different nodesnoneyesShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSynchronous replication via RaftMulti-source replication between multi datacentersInternal replication in Colossus, and regional replication between two clusters in different zonesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesyes
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)
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDACIDAtomic single-row operationsno
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.nonono
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesno 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)no

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More resources
DatabendDgraphEsgynDBGoogle Cloud BigtableSpark SQL
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