DB-EnginesextremeDB - Data management wherever you need itEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by Redgate Software

DBMS > Apache Impala vs. eXtremeDB vs. IRONdb vs. Microsoft Azure Table Storage vs. Rockset

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

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisoneXtremeDB  Xexclude from comparisonIRONdb  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonRockset  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionAnalytic DBMS for HadoopNatively in-memory DBMS with options for persistency, high-availability and clusteringA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityA Wide Column Store for rapid development using massive semi-structured datasetsA scalable, reliable search and analytics service in the cloud, built on RocksDB
Primary database modelRelational DBMSRelational DBMS
Time Series DBMS
Time Series DBMSWide column storeDocument store
Secondary database modelsDocument storeRelational DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score10.63
Rank#40  Overall
#24  Relational DBMS
Score0.79
Rank#212  Overall
#100  Relational DBMS
#18  Time Series DBMS
Score3.55
Rank#80  Overall
#6  Wide column stores
Score1.07
Rank#180  Overall
#31  Document stores
Websiteimpala.apache.orgwww.mcobject.comwww.circonus.com/solutions/time-series-database/azure.microsoft.com/­en-us/­services/­storage/­tablesrockset.com
Technical documentationimpala.apache.org/­impala-docs.htmlwww.mcobject.com/­docs/­extremedb.htmdocs.circonus.com/irondb/category/getting-starteddocs.rockset.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaMcObjectCirconus LLC.MicrosoftRockset
Initial release20132001201720122019
Current release4.1.0, June 20228.2, 2021V0.10.20, January 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C and C++C and C++C++
Server operating systemsLinuxAIX
HP-UX
Linux
macOS
Solaris
Windows
Linuxhostedhosted
Data schemeyesyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyes infotext, numeric, histogramsyesdynamic typing
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 infosupport of XML interfaces availablenonono infoingestion from XML files supported
Secondary indexesyesyesnonoall fields are automatically indexed
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infowith the option: eXtremeSQLSQL-like query language (Circonus Analytics Query Language: CAQL)noRead-only SQL queries, including JOINs
APIs and other access methodsJDBC
ODBC
.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
HTTP APIRESTful HTTP APIHTTP REST
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C#
C++
Java
Lua
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
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesyes, in Luanono
Triggersnoyes infoby defining eventsnonono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning / shardingAutomatic, metric affinity per nodeSharding infoImplicit feature of the cloud serviceAutomatic sharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorActive Replication Fabric™ for IoT
Multi-source replication infoby means of eXtremeDB Cluster option
Source-replica replication infoby means of eXtremeDB High Availability option
configurable replication factor, datacenter awareyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate consistency per node, eventual consistency across nodesImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnooptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesyes infoOptimistic (MVCC) and pessimistic (locking) strategies availableyesyesyes
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.noyesnono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosnoAccess rights based on private key authentication or shared access signaturesAccess rights for users and organizations can be defined via Rockset console

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 ImpalaeXtremeDBIRONdbMicrosoft Azure Table StorageRockset
Recent citations in the news

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

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

Cloudera brings Apache Iceberg data lake format to its Data Platform
30 June 2022, SiliconANGLE News

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

McObject
17 November 2021, Electronic Design

Latest embedded DBMS supports asymmetric multiprocessing systems
24 May 2023, Embedded

The Data in Hard Real-time SCADA Systems Lets Companies Do More with Less
11 August 2023, Automation.com

Interview: Jeff Chang And Steve Graves Cover In-Memory Databases
17 December 2013, Electronic Design

Schneider Electric to collaborate with McObject
14 October 2015, Construction Week Online

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, Microsoft

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

OpenAI’s first acquisition is an enterprise data startup
21 June 2024, The Verge

OpenAI Looks To Boost Data Retrieval Capabilities Of Its GenAI Technology With Rockset Acquisition
26 June 2024, CRN

OpenAI acquires Rockset to enhance ChatGPT real-time data processing
25 June 2024, InfoWorld

An Analysis Of OpenAI’s Acquisition Of Rockset And Its Strategic Significance
24 June 2024, Forbes

OpenAI Buys Enterprise Startup to Help Customers Sift Through Data
21 June 2024, Bloomberg

provided by Google News



Share this page

Featured Products

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

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.

SingleStore logo

The data platform to build your intelligent applications.
Try it free.

Present your product here