DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Hive vs. QuestDB vs. ReductStore vs. Tkrzw

System Properties Comparison Hive vs. QuestDB vs. ReductStore vs. Tkrzw

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameHive  Xexclude from comparisonQuestDB  Xexclude from comparisonReductStore  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
Descriptiondata warehouse software for querying and managing large distributed datasets, built on HadoopA high performance open source SQL database for time series dataDesigned to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.A 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 DBMSTime Series DBMSTime Series DBMSKey-value store
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score2.70
Rank#105  Overall
#8  Time Series DBMS
Score0.05
Rank#384  Overall
#44  Time Series DBMS
Score0.07
Rank#372  Overall
#57  Key-value stores
Websitehive.apache.orgquestdb.iogithub.com/­reductstore
www.reduct.store
dbmx.net/­tkrzw
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homequestdb.io/­docswww.reduct.store/­docs
DeveloperApache Software Foundation infoinitially developed by FacebookQuestDB Technology IncReductStore LLCMikio Hirabayashi
Initial release2012201420232020
Current release3.1.3, April 20221.9, March 20240.9.3, August 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache 2.0Open Source infoBusiness Source License 1.1Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava (Zero-GC), C++, RustC++, RustC++
Server operating systemsAll OS with a Java VMLinux
macOS
Windows
Docker
Linux
macOS
Windows
Linux
macOS
Data schemeyesyes infoschema-free via InfluxDB Line Protocolschema-free
Typing infopredefined data types such as float or dateyesyesno
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
Secondary indexesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL with time-series extensionsno
APIs and other access methodsJDBC
ODBC
Thrift
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
HTTP API
Supported programming languagesC++
Java
PHP
Python
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
C++
JavaScript (Node.js)
Python
Rust
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by timestamps)none
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replication with eventual consistencynone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID for single-table writes
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infothrough memory mapped filesyes infousing specific database classes
User concepts infoAccess controlAccess rights for users, groups and rolesno
More information provided by the system vendor
HiveQuestDBReductStoreTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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
News

Fluid real-time dashboards with Grafana and QuestDB
11 June 2024

QuestDB 8.0: Major Release
23 May 2024

QuestDB and Raspberry Pi 5 benchmark, a pocket-sized powerhouse
8 May 2024

Build your own resource monitor with QuestDB and Grafana
6 May 2024

Does "vpmovzxbd" Scare You? Here's Why it Doesn't Have To
12 April 2024

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

Why is Hadoop not listed in the DB-Engines Ranking?
13 May 2013, Paul Andlinger

show all

Recent citations in the news

Apache Software Foundation Announces Apache Hive 4.0
30 April 2024, Datanami

Design a data mesh pattern for Amazon EMR-based data lakes using AWS Lake Formation with Hive metastore ...
10 June 2024, AWS Blog

18 Top Big Data Tools and Technologies to Know About in 2024
24 January 2024, TechTarget

ASF Unveils the Next Evolution of Big Data Processing With the Launch of Hive 4.0
2 May 2024, Datanami

Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS | Amazon Web Services
18 October 2023, AWS Blog

provided by Google News

QuestDB snares $12M Series A with hosted version coming soon
3 November 2021, TechCrunch

SQL Extensions for Time-Series Data in QuestDB
11 January 2021, Towards Data Science

Comparing Different Time-Series Databases
10 February 2022, hackernoon.com

QuestDB Raises $12M in Series A Funding
8 November 2021, FinSMEs

Aquis Exchange goes live with QuestDB for real time monitoring
2 November 2022, FinanceFeeds

provided by Google News



Share this page

Featured Products

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.

Present your product here