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DBMS > Apache Impala vs. FatDB vs. Google Cloud Datastore vs. NuoDB vs. ToroDB

System Properties Comparison Apache Impala vs. FatDB vs. Google Cloud Datastore vs. NuoDB vs. ToroDB

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonFatDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonNuoDB  Xexclude from comparisonToroDB  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionAnalytic DBMS for HadoopA .NET NoSQL DBMS that can integrate with and extend SQL Server.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformNuoDB is a webscale distributed database that supports SQL and ACID transactionsA MongoDB-compatible JSON document store, built on top of PostgreSQL
Primary database modelRelational DBMSDocument store
Key-value store
Document storeRelational DBMSDocument 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
Score4.36
Rank#72  Overall
#12  Document stores
Score0.94
Rank#197  Overall
#92  Relational DBMS
Websiteimpala.apache.orgcloud.google.com/­datastorewww.3ds.com/­nuodb-distributed-sql-databasegithub.com/­torodb/­server
Technical documentationimpala.apache.org/­impala-docs.htmlcloud.google.com/­datastore/­docsdoc.nuodb.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaFatCloudGoogleDassault Systèmes infooriginally NuoDB, Inc.8Kdata
Initial release20132012200820132016
Current release4.1.0, June 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialcommercial infolimited edition freeOpen Source infoAGPL-V3
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 languageC++C#C++Java
Server operating systemsLinuxWindowshostedhosted infoAmazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows
All OS with a Java 7 VM
Data schemeyesschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesyes, details hereyesyes infostring, integer, double, boolean, date, object_id
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 indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsno infoVia inetgration in SQL ServerSQL-like query language (GQL)yes
APIs and other access methodsJDBC
ODBC
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC#.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C++
Go
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes infovia applicationsusing Google App EngineJava, SQL
Triggersnoyes infovia applicationsCallbacks using the Google Apps Engineyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingdata is dynamically stored/cached on the nodes where it is read/writtenSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorselectable replication factorMulti-source replication using Paxosyes infoManaged transparently by NuoDBSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Immediate Consistency
Immediate 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
Immediate Consistency
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor pathsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID infotunable commit protocolno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoMVCCyes
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 infoTemporary table
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosno infoCan implement custom security layer via applicationsAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Standard SQL roles/ privileges, Administrative UsersAccess rights for users and roles

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More resources
Apache ImpalaFatDBGoogle Cloud DatastoreNuoDBToroDB
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