DBMS > Hive vs. Oracle NoSQL vs. RocksDB vs. SAP SQL Anywhere vs. TerarkDB

System Properties Comparison Hive vs. Oracle NoSQL vs. RocksDB vs. SAP SQL Anywhere vs. TerarkDB

Editorial information provided by DB-Engines

Name

Description

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

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

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

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

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

Relational DBMS

Document store
Key-value store
Relational DBMS

Key-value store

Relational DBMS

Key-value store

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

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

hive.apache.org

www.oracle.com/database/nosql/technologies/nosql

rocksdb.org

www.sap.com/products/technology-platform/sql-anywhere.html

github.com/bytedance/terarkdb

Technical documentation

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

docs.oracle.com/en/database/other-databases/nosql-database/index.html

github.com/facebook/rocksdb/wiki

help.sap.com/docs/SAP_SQL_Anywhere

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Apache Software Foundation

initially developed by Facebook

Oracle

Facebook, Inc.

SAP

formerly Sybase

ByteDance, originally Terark

Initial release

2012

2011

2013

1992

2016

Current release

3.1.3, April 2022

23.3, December 2023

9.2.1, May 2024

17, July 2015

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

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

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

Implementation language

Java

C++

Server operating systems

All OS with a Java VM

Linux
Solaris SPARC/x86

Linux

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

optional

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

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC
Thrift

RESTful HTTP API

C++ API
Java API

ADO.NET
HTTP API
JDBC
ODBC

C++ API
Java API

Supported programming languages

C++
Java
PHP
Python

C
C#
Go
Java
JavaScript (Node.js)
Python

C
C++
Go
Java
Perl
Python
Ruby

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

C++
Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes, in C/C++, Java, .Net or Perl

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

yes

Source-replica replication

Database mirroring

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

configurable

ACID within a storage node (=shard)

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

off heap cache

yes

User concepts

Access control

Access rights for users, groups and roles

Access rights for users and roles

fine grained access rights according to SQL-standard

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