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DBMS > Apache Impala vs. GridGain vs. Hive vs. QuestDB

System Properties Comparison Apache Impala vs. GridGain vs. Hive vs. QuestDB

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGridGain  Xexclude from comparisonHive  Xexclude from comparisonQuestDB  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopGridGain is an in-memory computing platform, built on Apache Ignitedata warehouse software for querying and managing large distributed datasets, built on HadoopA high performance open source SQL database for time series data
Primary database modelRelational DBMSKey-value store
Relational DBMS
Relational DBMSTime Series DBMS
Secondary database modelsDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score2.70
Rank#105  Overall
#8  Time Series DBMS
Websiteimpala.apache.orgwww.gridgain.comhive.apache.orgquestdb.io
Technical documentationimpala.apache.org/­impala-docs.htmlwww.gridgain.com/­docs/­index.htmlcwiki.apache.org/­confluence/­display/­Hive/­Homequestdb.io/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGridGain Systems, Inc.Apache Software Foundation infoinitially developed by FacebookQuestDB Technology Inc
Initial release2013200720122014
Current release4.1.0, June 2022GridGain 8.5.13.1.3, April 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoApache Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java, C++, .NetJavaJava (Zero-GC), C++, Rust
Server operating systemsLinuxLinux
OS X
Solaris
Windows
All OS with a Java VMLinux
macOS
Windows
Data schemeyesyesyesyes infoschema-free via InfluxDB Line Protocol
Typing infopredefined data types such as float or dateyesyesyesyes
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.noyesno
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsANSI-99 for query and DML statements, subset of DDLSQL-like DML and DDL statementsSQL with time-series extensions
APIs and other access methodsJDBC
ODBC
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
Thrift
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Supported programming languagesAll languages supporting JDBC/ODBCC#
C++
Java
PHP
Python
Ruby
Scala
C++
Java
PHP
Python
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes (compute grid and cache interceptors can be used instead)yes infouser defined functions and integration of map-reduceno
Triggersnoyes (cache interceptors and events)nono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardinghorizontal partitioning (by timestamps)
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes (replicated cache)selectable replication factorSource-replica replication with eventual consistency
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyes (compute grid and hadoop accelerator)yes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID for single-table writes
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.noyesyes infothrough memory mapped files
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosSecurity Hooks for custom implementationsAccess rights for users, groups and roles
More information provided by the system vendor
Apache ImpalaGridGainHiveQuestDB
Specific characteristicsRelational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantagesHigh ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFinancial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersBanks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Licensing and pricing modelsOpen source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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More resources
Apache ImpalaGridGainHiveQuestDB
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