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DBMS > Dgraph vs. EsgynDB vs. Google Cloud Datastore vs. Sadas Engine vs. Solr

System Properties Comparison Dgraph vs. EsgynDB vs. Google Cloud Datastore vs. Sadas Engine vs. Solr

Editorial information provided by DB-Engines
NameDgraph  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonSadas Engine  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionDistributed and scalable native Graph DBMSEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelGraph DBMSRelational DBMSDocument storeRelational DBMSSearch 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
Score4.47
Rank#76  Overall
#12  Document stores
Score0.00
Rank#383  Overall
#158  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Websitedgraph.iowww.esgyn.cncloud.google.com/­datastorewww.sadasengine.comsolr.apache.org
Technical documentationdgraph.io/­docscloud.google.com/­datastore/­docswww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationsolr.apache.org/­resources.html
DeveloperDgraph Labs, Inc.EsgynGoogleSADAS s.r.l.Apache Software Foundation
Initial release20162015200820062006
Current release8.09.6.0, April 2024
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialcommercial infofree trial version availableOpen 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
LinuxhostedAIX
Linux
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeschema-freeyesschema-freeyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesyes, details hereyesyes 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 indexesyesyesyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLnoyesSQL-like query language (GQL)yesSolr 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
RESTful HTTP/JSON API
JDBC
ODBC
Proprietary protocol
Java API
RESTful HTTP/JSON API
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
All languages supporting JDBC/ODBC/ADO.Net.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C#
C++
Groovy
Java
PHP
Python
.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 Proceduresusing Google App EnginenoJava plugins
TriggersnonoCallbacks using the Google Apps Enginenoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesyesShardingShardinghorizontal partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSynchronous replication via RaftMulti-source replication between multi datacentersMulti-source replication using Paxosnoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infousing Google Cloud Dataflownospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesyes infovia ReferenceProperties or Ancestor pathsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsoptimistic locking
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.nonoyes infomanaged by 'Learn by Usage'yes
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)Access rights for users, groups and roles according to SQL-standardyes

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More resources
DgraphEsgynDBGoogle Cloud DatastoreSadas EngineSolr
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