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DBMS > Dgraph vs. EsgynDB vs. Google Cloud Bigtable vs. LevelDB vs. Solr

System Properties Comparison Dgraph vs. EsgynDB vs. Google Cloud Bigtable vs. LevelDB vs. Solr

Editorial information provided by DB-Engines
NameDgraph  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonLevelDB  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionDistributed 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.Embeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelGraph DBMSRelational DBMSKey-value store
Wide column store
Key-value storeSearch engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
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
Score2.35
Rank#111  Overall
#19  Key-value stores
Score42.91
Rank#24  Overall
#3  Search engines
Websitedgraph.iowww.esgyn.cncloud.google.com/­bigtablegithub.com/­google/­leveldbsolr.apache.org
Technical documentationdgraph.io/­docscloud.google.com/­bigtable/­docsgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mdsolr.apache.org/­resources.html
DeveloperDgraph Labs, Inc.EsgynGoogleGoogleApache Software Foundation
Initial release20162015201520112006
Current release1.23, February 20219.6.0, April 2024
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialOpen Source infoBSDOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC++, JavaC++Java
Server operating systemsLinux
OS X
Windows
LinuxhostedIllumos
Linux
OS X
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeschema-freeyesschema-freeschema-freeyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesnonoyes infosupports customizable data types and automatic typing
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.nonononoyes
Secondary indexesyesyesnonoyes infoAll search fields are automatically indexed
SQL infoSupport of SQLnoyesnonoSolr Parallel SQL Interface
APIs and other access methodsGraphQL 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)
Java API
RESTful HTTP/JSON API
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
All languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnoJava Stored ProceduresnonoJava plugins
Triggersnonononoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesyesShardingShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSynchronous replication via RaftMulti-source replication between multi datacentersInternal replication in Colossus, and regional replication between two clusters in different zonesnoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesnospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
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)Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDAtomic single-row operationsnooptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infowith automatic compression on writesyes
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, groups and roles based on Google Cloud Identity and Access Management (IAM)noyes

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More resources
DgraphEsgynDBGoogle Cloud BigtableLevelDBSolr
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