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DBMS > EsgynDB vs. Google Cloud Bigtable vs. H2 vs. Solr

System Properties Comparison EsgynDB vs. Google Cloud Bigtable vs. H2 vs. Solr

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonH2  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.Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.A widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSKey-value store
Wide column store
Relational DBMSSearch engine
Secondary database modelsSpatial DBMSSpatial 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
Score8.13
Rank#49  Overall
#31  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Websitewww.esgyn.cncloud.google.com/­bigtablewww.h2database.comsolr.apache.org
Technical documentationcloud.google.com/­bigtable/­docswww.h2database.com/­html/­main.htmlsolr.apache.org/­resources.html
DeveloperEsgynGoogleThomas MuellerApache Software Foundation
Initial release2015201520052006
Current release2.2.220, July 20239.6.0, April 2024
License infoCommercial or Open SourcecommercialcommercialOpen Source infodual-licence (Mozilla public license, Eclipse public license)Open 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 VMAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesschema-freeyesyes 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 SQLyesnoyesSolr Parallel SQL Interface
APIs and other access methodsADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Java API
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
Java.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 Stored Procedures and User-Defined FunctionsJava plugins
Triggersnonoyesyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding
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 zonesWith clustering: 2 database servers on different computers operate on identical copies of a databaseyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesnospark-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)Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsACIDoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
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.nonoyesyes
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)fine grained access rights according to SQL-standardyes

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More resources
EsgynDBGoogle Cloud BigtableH2Solr
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