DBMS > FeatureBase vs. Hive vs. TDSQL for MySQL vs. Tkrzw

System Properties Comparison FeatureBase vs. Hive vs. TDSQL for MySQL vs. Tkrzw

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Editorial information provided by DB-Engines

Name

Description

Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.

data warehouse software for querying and managing large distributed datasets, built on Hadoop

A high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.

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 model

Relational DBMS

Key-value store

Secondary database models

Document store
Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.31
Rank	#292	Overall
	#135	Relational DBMS

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	0.85
Rank	#207	Overall
	#97	Relational DBMS

Score	0.07
Rank	#372	Overall
	#57	Key-value stores

Website

www.featurebase.com

hive.apache.org

www.tencentcloud.com/products/dcdb

dbmx.net/tkrzw

Technical documentation

docs.featurebase.com

cwiki.apache.org/confluence/display/Hive/Home

www.tencentcloud.com/document/product/1042

Developer

Molecula and Pilosa Open Source Contributors

Apache Software Foundation

initially developed by Facebook

Tencent

Mikio Hirabayashi

Initial release

2017

2012

2013

2020

Current release

2022, May 2022

3.1.3, April 2022

0.9.3, August 2020

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

commercial

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++

Server operating systems

Linux
macOS

All OS with a Java VM

hosted

Linux
macOS

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

SQL

Support of SQL

SQL queries

SQL-like DML and DDL statements

yes

APIs and other access methods

gRPC
JDBC
Kafka Connector
ODBC

JDBC
ODBC
Thrift

JDBC
ODBC

Supported programming languages

Java
Python

C++
Java
PHP
Python

C
C#
C++
Java
PHP
Python
Ruby

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes, using Linux fsync

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using specific database classes

User concepts

Access control

Access rights for users, groups and roles

Users with fine-grained authorization concept

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More resources

DB-Engines blog posts

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

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