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DBMS > EsgynDB vs. Google Cloud Bigtable vs. OrientDB vs. Solr

System Properties Comparison EsgynDB vs. Google Cloud Bigtable vs. OrientDB vs. Solr

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonOrientDB  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionEnterprise-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.Multi-model DBMS (Document, Graph, Key/Value)A widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSKey-value store
Wide column store
Document store
Graph DBMS
Key-value store
Search engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score3.19
Rank#93  Overall
#16  Document stores
#7  Graph DBMS
#14  Key-value stores
Score42.91
Rank#24  Overall
#3  Search engines
Websitewww.esgyn.cncloud.google.com/­bigtableorientdb.orgsolr.apache.org
Technical documentationcloud.google.com/­bigtable/­docswww.orientdb.com/­docs/­last/­index.htmlsolr.apache.org/­resources.html
DeveloperEsgynGoogleOrientDB LTD; CallidusCloud; SAPApache Software Foundation
Initial release2015201520102006
Current release3.2.29, March 20249.6.0, April 2024
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache version 2Open Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaJavaJava
Server operating systemsLinuxhostedAll OS with a Java JDK (>= JDK 6)All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesschema-freeschema-free infoSchema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")yes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesnoyesyes 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.nononoyes
Secondary indexesyesnoyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLyesnoSQL-like query language, no joinsSolr Parallel SQL Interface
APIs and other access methodsADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API
Java API
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresJava Stored ProceduresnoJava, JavascriptJava plugins
TriggersnonoHooksyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesno infocould be achieved with distributed queriesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistency
Foreign keys infoReferential integrityyesnoyes inforelationship in graphsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsACIDoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlfine 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 and roles; record level security configurableyes

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More resources
EsgynDBGoogle Cloud BigtableOrientDBSolr
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