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 > BoltDB vs. DuckDB vs. HBase vs. Heroic

System Properties Comparison BoltDB vs. DuckDB vs. HBase vs. Heroic

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameBoltDB  Xexclude from comparisonDuckDB  Xexclude from comparisonHBase  Xexclude from comparisonHeroic  Xexclude from comparison
DescriptionAn embedded key-value store for Go.An embeddable, in-process, column-oriented SQL OLAP RDBMSWide-column store based on Apache Hadoop and on concepts of BigTableTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch
Primary database modelKey-value storeRelational DBMSWide column storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.74
Rank#220  Overall
#31  Key-value stores
Score4.57
Rank#74  Overall
#40  Relational DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Websitegithub.com/­boltdb/­boltduckdb.orghbase.apache.orggithub.com/­spotify/­heroic
Technical documentationduckdb.org/­docshbase.apache.org/­book.htmlspotify.github.io/­heroic
DeveloperApache Software Foundation infoApache top-level project, originally developed by PowersetSpotify
Initial release2013201820082014
Current release0.10, February 20242.3.4, January 2021
License infoCommercial or Open SourceOpen Source infoMIT LicenseOpen Source infoMIT LicenseOpen 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

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC++JavaJava
Server operating systemsBSD
Linux
OS X
Solaris
Windows
server-lessLinux
Unix
Windows infousing Cygwin
Data schemeschema-freeyesschema-free, schema definition possibleschema-free
Typing infopredefined data types such as float or datenoyesoptions to bring your own types, AVROyes
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.nononono
Secondary indexesnoyesnoyes infovia Elasticsearch
SQL infoSupport of SQLnoyesnono
APIs and other access methodsArrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC
Java API
RESTful HTTP API
Thrift
HQL (Heroic Query Language, a JSON-based language)
HTTP API
Supported programming languagesGoC
C# info3rd party driver
C++
Crystal info3rd party driver
Go info3rd party driver
Java
Lisp info3rd party driver
Python
R
Ruby info3rd party driver
Rust
Swift
Zig info3rd party driver
C
C#
C++
Groovy
Java
PHP
Python
Scala
Server-side scripts infoStored proceduresnonoyes infoCoprocessors in Javano
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesnonenoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnonenoneMulti-source replication
Source-replica replication
yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate Consistency or Eventual ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDSingle row ACID (across millions of columns)no
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes
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.noyesyesno
User concepts infoAccess controlnonoAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

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
BoltDBDuckDBHBaseHeroic
DB-Engines blog posts

Cloudera's HBase PaaS offering now supports Complex Transactions
11 August 2021,  Krishna Maheshwari (sponsor) 

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

show all

Recent citations in the news

4 Instructive Postmortems on Data Downtime and Loss
1 March 2024, The Hacker News

Grafana Loki: Architecture Summary and Running in Kubernetes
14 March 2023, hackernoon.com

Roblox’s cloud-native catastrophe: A post mortem
31 January 2022, InfoWorld

How to Put a GUI on Ansible, Using Semaphore
22 April 2023, The New Stack

provided by Google News

My First Billion (of Rows) in DuckDB | by João Pedro | May, 2024
1 May 2024, Towards Data Science

Enabling Remote Query Execution through DuckDB Extensions
12 March 2024, InfoQ.com

DuckDB Walks to the Beat of Its Own Analytics Drum
5 March 2024, Datanami

DuckDB and AWS — How to Aggregate 100 Million Rows in 1 Minute
25 April 2024, Towards Data Science

MotherDuck Raises $52.5 Million Series B Funding as DuckDB Adoption Soars
20 September 2023, PR Newswire

provided by Google News

Best Practices from Rackspace for Modernizing a Legacy HBase/Solr Architecture Using AWS Services | Amazon Web ...
9 October 2023, AWS Blog

Less Components, Higher Performance: Apache Doris instead of ClickHouse, MySQL, Presto, and HBase
20 October 2023, hackernoon.com

HBase: The database big data left behind
6 May 2016, InfoWorld

What Is HBase? (Definition, Uses, Benefits, Features)
22 December 2022, Built In

HBase Tutorial
24 February 2023, Simplilearn

provided by Google News

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

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

SingleStore logo

Build AI apps with Vectors on SQL and JSON with milliseconds response times.
Try it today.

Neo4j logo

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

Milvus logo

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

Present your product here