DBMS > LevelDB vs. Oracle NoSQL vs. SpaceTime vs. SWC-DB

System Properties Comparison LevelDB vs. Oracle NoSQL vs. SpaceTime vs. SWC-DB

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Editorial information provided by DB-Engines

Name

Description

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

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

SpaceTime is a spatio-temporal DBMS with a focus on performance.

A high performance, scalable Wide Column DBMS

Primary database model

Key-value store

Document store
Key-value store
Relational DBMS

Spatial DBMS

Wide column store

Secondary database models

Relational DBMS

Time Series DBMS

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

Score	2.25
Rank	#115	Overall
	#19	Key-value stores

Score	3.05
Rank	#97	Overall
	#17	Document stores
	#16	Key-value stores
	#50	Relational DBMS

Score	0.03
Rank	#392	Overall
	#8	Spatial DBMS

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Website

github.com/google/leveldb

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

www.mireo.com/spacetime

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

github.com/google/leveldb/blob/main/doc/index.md

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

Developer

Google

Oracle

Mireo

Alex Kashirin

Initial release

2011

2020

Current release

1.23, February 2021

24.1, May 2024

0.5, April 2021

License

Commercial or Open Source

Open Source

BSD

Open Source

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

commercial

Open Source

GPL V3

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

C++

Java

C++

Server operating systems

Illumos
Linux
OS X
Windows

Linux
Solaris SPARC/x86

Linux

Data scheme

schema-free

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

yes

schema-free

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

A subset of ANSI SQL is implemented

SQL-like query language

APIs and other access methods

RESTful HTTP API

Proprietary protocol
Thrift

Supported programming languages

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

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

C#
C++
Python

C++

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Fixed-grid hypercubes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

Real-time block device replication (DRBD)

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

configurable

ACID within a storage node (=shard)

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

yes

In-memory capabilities

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

yes

off heap cache

User concepts

Access control

Access rights for users and roles

yes

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