DBMS > Heroic vs. LeanXcale vs. LevelDB vs. Linter vs. SpatiaLite

System Properties Comparison Heroic vs. LeanXcale vs. LevelDB vs. Linter vs. SpatiaLite

Editorial information provided by DB-Engines

Name

Description

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

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

RDBMS for high security requirements

Spatial extension of SQLite

Primary database model

Time Series DBMS

Key-value store
Relational DBMS

Key-value store

Relational DBMS

Spatial DBMS

Secondary database models

Spatial DBMS

Relational DBMS

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

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	0.36
Rank	#280	Overall
	#40	Key-value stores
	#129	Relational DBMS

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

Score	0.12
Rank	#350	Overall
	#152	Relational DBMS

Score	1.63
Rank	#146	Overall
	#3	Spatial DBMS

Website

github.com/spotify/heroic

www.leanxcale.com

github.com/google/leveldb

linter.ru

www.gaia-gis.it/fossil/libspatialite/index

Technical documentation

spotify.github.io/heroic

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

www.gaia-gis.it/gaia-sins/spatialite_topics.html

Developer

Spotify

LeanXcale

Google

relex.ru

Alessandro Furieri

Initial release

2014

2015

2011

1990

2008

Current release

1.23, February 2021

5.0.0, August 2020

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

BSD

commercial

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

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++

C and C++

C++

Server operating systems

Illumos
Linux
OS X
Windows

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

server-less

Data scheme

schema-free

yes

schema-free

yes

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

yes

via Elasticsearch

yes

SQL

Support of SQL

yes

through Apache Derby

yes

APIs and other access methods

HQL (Heroic Query Language, a JSON-based language)
HTTP API

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

Supported programming languages

C
Java
Scala

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

Server-side scripts

Stored procedures

yes

proprietary syntax with the possibility to convert from PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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

fine grained access rights according to SQL-standard

More information provided by the system vendor

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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