DBMS > LevelDB vs. RavenDB vs. SWC-DB vs. XTDB

System Properties Comparison LevelDB vs. RavenDB vs. SWC-DB vs. XTDB

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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

Open Source Operational and Transactional Enterprise NoSQL Document Database

A high performance, scalable Wide Column DBMS

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

Time Series DBMS

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

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	2.92
Rank	#101	Overall
	#18	Document stores

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

github.com/google/leveldb

ravendb.net

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

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

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

ravendb.net/docs

www.xtdb.com/docs

Developer

Google

Hibernating Rhinos

Alex Kashirin

Juxt Ltd.

Initial release

2011

2010

2020

2019

Current release

1.23, February 2021

5.4, July 2022

0.5, April 2021

1.19, September 2021

License

Commercial or Open Source

Open Source

BSD

Open Source

AGPL version 3, commercial license available

Open Source

GPL V3

Open Source

MIT License

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++

Clojure

Server operating systems

Illumos
Linux
OS X
Windows

Linux
macOS
Raspberry Pi
Windows

Linux

All OS with a Java 8 (and higher) VM
Linux

Data scheme

schema-free

Typing

predefined data types such as float or date

yes, extensible-data-notation format

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 query language (RQL)

SQL-like query language

limited SQL, making use of Apache Calcite

APIs and other access methods

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

Proprietary protocol
Thrift

HTTP REST
JDBC

Supported programming languages

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

C++

Clojure
Java

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID, Cluster-wide transaction available

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

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

User concepts

Access control

Authorization levels configured per client per database

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