DB-EnginesExtremeDB for everyone with an RTOSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Apache Impala vs. Drizzle vs. IRONdb vs. STSdb vs. Tkrzw

System Properties Comparison Apache Impala vs. Drizzle vs. IRONdb vs. STSdb vs. Tkrzw

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDrizzle  Xexclude from comparisonIRONdb  Xexclude from comparisonSTSdb  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionAnalytic DBMS for HadoopMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityKey-Value Store with special method for indexing infooptimized for high performance using a special indexing methodA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelRelational DBMSRelational DBMSTime Series DBMSKey-value storeKey-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
Score0.04
Rank#360  Overall
#52  Key-value stores
Score0.00
Rank#383  Overall
#60  Key-value stores
Websiteimpala.apache.orgwww.circonus.com/solutions/time-series-database/github.com/­STSSoft/­STSdb4dbmx.net/­tkrzw
Technical documentationimpala.apache.org/­impala-docs.htmldocs.circonus.com/irondb/category/getting-started
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDrizzle project, originally started by Brian AkerCirconus LLC.STS Soft SCMikio Hirabayashi
Initial release20132008201720112020
Current release4.1.0, June 20227.2.4, September 2012V0.10.20, January 20184.0.8, September 20150.9.3, August 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoGNU GPLcommercialOpen Source infoGPLv2, commercial license availableOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++C and C++C#C++
Server operating systemsLinuxFreeBSD
Linux
OS X
LinuxWindowsLinux
macOS
Data schemeyesyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesyes infotext, numeric, histogramsyes infoprimitive types and user defined types (classes)no
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 indexesyesyesnono
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infowith proprietary extensionsSQL-like query language (Circonus Analytics Query Language: CAQL)nono
APIs and other access methodsJDBC
ODBC
JDBCHTTP API.NET Client API
Supported programming languagesAll languages supporting JDBC/ODBCC
C++
Java
PHP
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
C#
Java
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyes, in Luanono
Triggersnono infohooks for callbacks inside the server can be used.nonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingAutomatic, metric affinity per nodenonenone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication
Source-replica replication
configurable replication factor, datacenter awarenonenone
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 consistency per node, eventual consistency across nodesImmediate Consistency
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.nonoyes infousing specific database classes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosPluggable authentication mechanisms infoe.g. LDAP, HTTPnonono

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 ImpalaDrizzleIRONdbSTSdbTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
DB-Engines blog posts

MySQL won the April ranking; did its forks follow?
1 April 2015, Paul Andlinger

Has MySQL finally lost its mojo?
1 July 2013, Matthias Gelbmann

show all

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

StarRocks Brings Speedy OLAP Database to the Cloud
14 July 2022, 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

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

Apica Acquires Telemetry Data Management Pioneer Circonus And Lands New Funding
22 February 2024, Datanami

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

provided by Google News



Share this page

Featured Products

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.

Neo4j logo

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

SingleStore logo

The database to transact, analyze and contextualize your data in real time.
Try it today.

Present your product here