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

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

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonEsgynDB  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonTrafodion  Xexclude from comparison
Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
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.Transactional SQL-on-Hadoop DBMS
Primary database modelRelational DBMSRelational DBMSDocument storeKey-value store
Wide column store
Relational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score10.63
Rank#40  Overall
#24  Relational DBMS
Score0.15
Rank#325  Overall
#144  Relational DBMS
Score13.60
Rank#39  Overall
#6  Document stores
Score2.97
Rank#92  Overall
#15  Key-value stores
#8  Wide column stores
Websiteimpala.apache.orgwww.esgyn.cnfirebase.google.com/­products/­realtime-databasecloud.google.com/­bigtabletrafodion.apache.org
Technical documentationimpala.apache.org/­impala-docs.htmlfirebase.google.com/­docs/­databasecloud.google.com/­bigtable/­docstrafodion.apache.org/­documentation.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaEsgynGoogle infoacquired by Google 2014GoogleApache Software Foundation, originally developed by HP
Initial release20132015201220152014
Current release4.1.0, June 20222.3.0, February 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++, JavaC++, Java
Server operating systemsLinuxLinuxhostedhostedLinux
Data schemeyesyesschema-freeschema-freeyes
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.nonononono
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesnonoyes
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)
ADO.NET
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCAll languages supporting JDBC/ODBC/ADO.NetJava
JavaScript
Objective-C
C#
C++
Go
Java
JavaScript (Node.js)
Python
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceJava Stored Procedureslimited functionality with using 'rules'noJava Stored Procedures
TriggersnonoCallbacks are triggered when data changesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
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 zonesyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesnoyesyes infovia user defined functions and HBase
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)Immediate Consistency
Foreign keys infoReferential integritynoyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDyesAtomic single-row operationsACID
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.nononono
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)fine grained access rights according to SQL-standard

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More resources
Apache ImpalaEsgynDBFirebase Realtime DatabaseGoogle Cloud BigtableTrafodion
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