DB-EnginesExtremeDB: mitigate connectivity issues in a DBMSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Apache Impala vs. atoti vs. BigObject vs. FatDB

System Properties Comparison Apache Impala vs. atoti vs. BigObject vs. FatDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonatoti  Xexclude from comparisonBigObject  Xexclude from comparisonFatDB  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionAnalytic DBMS for HadoopAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.Analytic DBMS for real-time computations and queriesA .NET NoSQL DBMS that can integrate with and extend SQL Server.
Primary database modelRelational DBMSObject oriented DBMSRelational DBMS infoa hierachical model (tree) can be imposedDocument store
Key-value store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.56
Rank#245  Overall
#10  Object oriented DBMS
Score0.13
Rank#333  Overall
#147  Relational DBMS
Websiteimpala.apache.orgatoti.iobigobject.io
Technical documentationimpala.apache.org/­impala-docs.htmldocs.atoti.iodocs.bigobject.io
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaActiveViamBigObject, Inc.FatCloud
Initial release201320152012
Current release4.1.0, June 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infofree versions availablecommercial infofree community edition availablecommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaC#
Server operating systemsLinuxLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
Windows
Data schemeyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyes
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.nono
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsMultidimensional Expressions (MDX)SQL-like DML and DDL statementsno infoVia inetgration in SQL Server
APIs and other access methodsJDBC
ODBC
fluentd
ODBC
RESTful HTTP API
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
Supported programming languagesAll languages supporting JDBC/ODBCC#
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducePythonLuayes infovia applications
Triggersnonoyes infovia applications
Partitioning methods infoMethods for storing different data on different nodesShardingSharding, horizontal partitioningnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencynoneEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyes infoautomatically between fact table and dimension tablesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yes infoRead/write lock on objects (tables, trees)yes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosnono infoCan implement custom security layer via applications

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Apache ImpalaatotiBigObjectFatDB
Recent citations in the news

Cloudera creates observability tool to help enterprises manage cloud costs
6 June 2023, SiliconANGLE News

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

provided by Google News

Best use of cloud: ActiveViam
28 November 2023, Risk.net

FRTB product of the year: ActiveViam
28 November 2023, Risk.net

provided by Google News



Share this page

Featured Products

SingleStore logo

Database for your real-time AI and Analytics Apps.
Try it today.

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Present your product here