DB-EnginesextremeDB - solve IoT connectivity disruptionsEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by Redgate Software

DBMS > Apache Impala vs. Hazelcast vs. IRONdb vs. Microsoft Azure Table Storage

System Properties Comparison Apache Impala vs. Hazelcast vs. IRONdb vs. Microsoft Azure Table Storage

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonHazelcast  Xexclude from comparisonIRONdb  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionAnalytic DBMS for HadoopA widely adopted in-memory data gridA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityA Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelRelational DBMSKey-value storeTime Series DBMSWide column store
Secondary database modelsDocument storeDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score10.63
Rank#40  Overall
#24  Relational DBMS
Score5.72
Rank#59  Overall
#6  Key-value stores
Score3.55
Rank#80  Overall
#6  Wide column stores
Websiteimpala.apache.orghazelcast.comwww.circonus.com/solutions/time-series-database/azure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationimpala.apache.org/­impala-docs.htmlhazelcast.org/­imdg/­docsdocs.circonus.com/irondb/category/getting-started
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaHazelcastCirconus LLC.Microsoft
Initial release2013200820172012
Current release4.1.0, June 20225.3.6, November 2023V0.10.20, January 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2; commercial licenses availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaC and C++
Server operating systemsLinuxAll OS with a Java VMLinuxhosted
Data schemeyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyes infotext, numeric, histogramsyes
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.noyes infothe object must implement a serialization strategynono
Secondary indexesyesyesnono
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query languageSQL-like query language (Circonus Analytics Query Language: CAQL)no
APIs and other access methodsJDBC
ODBC
JCache
JPA
Memcached protocol
RESTful HTTP API
HTTP APIRESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes infoEvent Listeners, Executor Servicesyes, in Luano
Triggersnoyes infoEventsnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingAutomatic, metric affinity per nodeSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes infoReplicated Mapconfigurable replication factor, datacenter awareyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate consistency per node, eventual consistency across nodesImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoone or two-phase-commit; repeatable reads; read commitednooptimistic locking
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.noyesnono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosRole-based access controlnoAccess rights based on private key authentication or shared access signatures

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 ImpalaHazelcastIRONdbMicrosoft Azure Table Storage
Recent citations in the news

Apache Impala 4 Supports Operator Multi-Threading
29 July 2021, iProgrammer

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

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

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

Updates & Upserts in Hadoop Ecosystem with Apache Kudu
27 October 2017, KDnuggets

provided by Google News

Hazelcast embraces vector search
30 July 2024, Blocks & Files

Hazelcast 5.4 real time data processing platform boosts AI and consistency
17 April 2024, VentureBeat

Event Stream Processing Market Exploring Future Growth 2023-2032 and Key Players - Cloudera, Inc., Hazelcast,
24 September 2024, EIN News

Hazelcast Expands Global Partner Program to Support Mission-Critical, AI Application Projects
20 August 2024, PR Newswire

Hazelcast Weaves Wider Logic Threads Through The Data Fabric
7 March 2024, Forbes

provided by Google News

Application observability firm Apica buys telemetry data startup Circonus and adds more funding
21 February 2024, SiliconANGLE News

Apica gets $6 million in funding and buys Circonus -
21 February 2024, Enterprise Times

provided by Google News

How to use Azure Table storage in .Net
10 July 2024, InfoWorld

Working with Azure to Use and Manage Data Lakes
23 July 2024, Simplilearn

Azure Cosmos DB Data Migration tool imports from Azure Table storage
5 May 2015, azure.microsoft.com

How to Use C# Azure.Data.Tables SDK with Azure Cosmos DB
9 July 2021, hackernoon.com

How to write data to Azure Table Store with an Azure Function
14 April 2017, Experts Exchange

provided by Google News



Share this page

Featured Products

Neo4j logo

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

SingleStore logo

The data platform to build your intelligent applications.
Try it 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

Milvus logo

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

RaimaDB logo

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

Present your product here