DBMS > GeoSpock vs. LeanXcale vs. LevelDB vs. RocksDB

System Properties Comparison GeoSpock vs. LeanXcale vs. LevelDB vs. RocksDB

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Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

Spatial and temporal data processing engine for extreme data scale

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

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

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

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Key-value store

Secondary database models

Time Series DBMS

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

Score	0.29
Rank	#291	Overall
	#41	Key-value stores
	#132	Relational DBMS

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

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

Website

geospock.com

www.leanxcale.com

github.com/google/leveldb

rocksdb.org

Technical documentation

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

github.com/facebook/rocksdb/wiki

Developer

GeoSpock

LeanXcale

Google

Facebook, Inc.

Initial release

2015

2011

2013

Current release

2.0, September 2019

1.23, February 2021

8.11.4, April 2024

License

Commercial or Open Source

commercial

Open Source

BSD

Open Source

BSD

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, Javascript

C++

Server operating systems

hosted

Illumos
Linux
OS X
Windows

Linux

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

temporal, categorical

SQL

Support of SQL

ANSI SQL for query only (using Presto)

yes

through Apache Derby

APIs and other access methods

JDBC

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

C++ API
Java API

Supported programming languages

C
Java
Scala

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

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

User concepts

Access control

Access rights for users can be defined per table

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