DBMS > Hive vs. RocksDB vs. Teradata vs. TerarkDB

System Properties Comparison Hive vs. RocksDB vs. Teradata vs. TerarkDB

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Editorial information provided by DB-Engines

Name

Description

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

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

A hybrid cloud data analytics software platform (Teradata Vantage)

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	44.87
Rank	#22	Overall
	#15	Relational DBMS

Score	0.08
Rank	#367	Overall
	#56	Key-value stores

Website

hive.apache.org

rocksdb.org

www.teradata.com

github.com/bytedance/terarkdb

Technical documentation

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

github.com/facebook/rocksdb/wiki

docs.teradata.com

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Apache Software Foundation

initially developed by Facebook

Facebook, Inc.

Teradata

ByteDance, originally Terark

Initial release

2012

2013

1984

2016

Current release

3.1.3, April 2022

9.2.1, May 2024

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

BSD

commercial

restricted open source version available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

All OS with a Java VM

Linux

hosted
Linux

Data scheme

yes

schema-free

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.

yes

Secondary indexes

yes

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

SQL-like DML and DDL statements

yes

SQL 2016 + extensions

APIs and other access methods

JDBC
ODBC
Thrift

C++ API
Java API

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

C++ API
Java API

Supported programming languages

C++
Java
PHP
Python

C
C++
Go
Java
Perl
Python
Ruby

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

C++
Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

Hashing

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

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

In-memory capabilities

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

yes

User concepts

Access control

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

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