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DBMS > Apache Impala vs. Coveo vs. HEAVY.AI vs. RavenDB

System Properties Comparison Apache Impala vs. Coveo vs. HEAVY.AI vs. RavenDB

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonCoveo  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonRavenDB  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopAI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code developmentA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareOpen Source Operational and Transactional Enterprise NoSQL Document Database
Primary database modelRelational DBMSSearch engineRelational DBMSDocument store
Secondary database modelsDocument storeSpatial DBMSGraph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score2.11
Rank#118  Overall
#11  Search engines
Score1.64
Rank#145  Overall
#67  Relational DBMS
Score2.84
Rank#101  Overall
#18  Document stores
Websiteimpala.apache.orgwww.coveo.comgithub.com/­heavyai/­heavydb
www.heavy.ai
ravendb.net
Technical documentationimpala.apache.org/­impala-docs.htmldocs.coveo.comdocs.heavy.airavendb.net/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaCoveoHEAVY.AI, Inc.Hibernating Rhinos
Initial release2013201220162010
Current release4.1.0, June 20225.10, January 20225.4, July 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoApache Version 2; enterprise edition availableOpen Source infoAGPL version 3, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++ and CUDAC#
Server operating systemsLinuxhostedLinuxLinux
macOS
Raspberry Pi
Windows
Data schemeyeshybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configurationyesschema-free
Typing infopredefined data types such as float or dateyesyesyesno
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.nonono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyesSQL-like query language (RQL)
APIs and other access methodsJDBC
ODBC
RESTful HTTP APIJDBC
ODBC
Thrift
Vega
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCC#
Java
JavaScript
Python
All languages supporting JDBC/ODBC/Thrift
Python
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenonoyes
Triggersnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingyesSharding infoRound robinSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesMulti-source replicationMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesnoACID, Cluster-wide transaction available
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.noyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosgranular access controls, API key management, content filtersfine grained access rights according to SQL-standardAuthorization levels configured per client per database

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More resources
Apache ImpalaCoveoHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022RavenDB
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