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DBMS > Databricks vs. Dgraph vs. EsgynDB vs. GridDB vs. LevelDB

System Properties Comparison Databricks vs. Dgraph vs. EsgynDB vs. GridDB vs. LevelDB

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonDgraph  Xexclude from comparisonEsgynDB  Xexclude from comparisonGridDB  Xexclude from comparisonLevelDB  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 TrafodionScalable in-memory time series database optimized for IoT and Big DataEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string values
Primary database modelDocument store
Relational DBMS
Graph DBMSRelational DBMSTime Series DBMSKey-value store
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.53
Rank#152  Overall
#15  Graph DBMS
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score2.25
Rank#115  Overall
#19  Key-value stores
Websitewww.databricks.comdgraph.iowww.esgyn.cngriddb.netgithub.com/­google/­leveldb
Technical documentationdocs.databricks.comdgraph.io/­docsdocs.griddb.netgithub.com/­google/­leveldb/­blob/­main/­doc/­index.md
DeveloperDatabricksDgraph Labs, Inc.EsgynToshiba CorporationGoogle
Initial release20132016201520132011
Current release5.1, August 20221.23, February 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoBSD
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoC++, JavaC++C++
Server operating systemshostedLinux
OS X
Windows
LinuxLinuxIllumos
Linux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyes infonumerical, string, blob, geometry, boolean, timestampno
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.yesnononono
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLwith Databricks SQLnoyesSQL92, SQL-like TQL (Toshiba Query Language)no
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
GraphQL query language
gRPC (using protocol buffers) API
HTTP API
ADO.NET
JDBC
ODBC
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
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)
Perl
PHP
Python
Ruby
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoJava Stored Proceduresnono
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesyesShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesSynchronous replication via RaftMulti-source replication between multi datacentersSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID at container levelno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infowith automatic compression on writes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlno infoPlanned for future releasesfine grained access rights according to SQL-standardAccess rights for users can be defined per databaseno
More information provided by the system vendor
DatabricksDgraphEsgynDBGridDBLevelDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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More resources
DatabricksDgraphEsgynDBGridDBLevelDB
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