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DBMS > Apache Impala vs. EsgynDB vs. Firebase Realtime Database vs. Google Cloud Bigtable vs. RDF4J

System Properties Comparison Apache Impala vs. EsgynDB vs. Firebase Realtime Database vs. Google Cloud Bigtable vs. RDF4J

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonEsgynDB  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelRelational DBMSRelational DBMSDocument storeKey-value store
Wide column store
RDF store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score13.64
Rank#39  Overall
#6  Document stores
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score0.74
Rank#222  Overall
#9  RDF stores
Websiteimpala.apache.orgwww.esgyn.cnfirebase.google.com/­products/­realtime-databasecloud.google.com/­bigtablerdf4j.org
Technical documentationimpala.apache.org/­impala-docs.htmlfirebase.google.com/­docs/­databasecloud.google.com/­bigtable/­docsrdf4j.org/­documentation
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaEsgynGoogle infoacquired by Google 2014GoogleSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release20132015201220152004
Current release4.1.0, June 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud servicenonoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++, JavaJava
Server operating systemsLinuxLinuxhostedhostedLinux
OS X
Unix
Windows
Data schemeyesyesschema-freeschema-freeyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesyesyesnoyes
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.nononono
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesnonono
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
ODBC
Android
iOS
JavaScript API
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesAll languages supporting JDBC/ODBCAll languages supporting JDBC/ODBC/ADO.NetJava
JavaScript
Objective-C
C#
C++
Go
Java
JavaScript (Node.js)
Python
Java
PHP
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceJava Stored Procedureslimited functionality with using 'rules'noyes
TriggersnonoCallbacks are triggered when data changesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication between multi datacentersInternal replication in Colossus, and regional replication between two clusters in different zonesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDyesAtomic single-row operationsACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoin-memory storage is supported as well
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardyes, based on authentication and database rulesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no

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More resources
Apache ImpalaEsgynDBFirebase Realtime DatabaseGoogle Cloud BigtableRDF4J infoformerly known as Sesame
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