DBMS > Heroic vs. Machbase Neo vs. RocksDB vs. SpatiaLite vs. TDSQL for MySQL

System Properties Comparison Heroic vs. Machbase Neo vs. RocksDB vs. SpatiaLite vs. TDSQL for MySQL

Editorial information provided by DB-Engines

Name

Description

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

TimeSeries DBMS for AIoT and BigData

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

Spatial extension of SQLite

A high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.

Primary database model

Secondary database models

Relational DBMS

Document store
Spatial DBMS

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

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	0.17
Rank	#337	Overall
	#30	Time Series DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	1.63
Rank	#146	Overall
	#3	Spatial DBMS

Score	0.85
Rank	#207	Overall
	#97	Relational DBMS

Website

github.com/spotify/heroic

machbase.com

rocksdb.org

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

www.tencentcloud.com/products/dcdb

Technical documentation

spotify.github.io/heroic

machbase.com/dbms

github.com/facebook/rocksdb/wiki

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

www.tencentcloud.com/document/product/1042

Developer

Spotify

Machbase

Facebook, Inc.

Alessandro Furieri

Tencent

Initial release

2014

2013

2008

2013

Current release

V8.0, August 2023

9.2.1, May 2024

5.0.0, August 2020

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

free test version available

Open Source

BSD

Open Source

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

commercial

Cloud-based only

Only available as a cloud service

yes

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

Linux
macOS
Windows

Linux

server-less

hosted

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

SQL-like query language

yes

APIs and other access methods

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

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

C++ API
Java API

JDBC
ODBC

Supported programming languages

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

C
C++
Go
Java
Perl
Python
Ruby

C
C#
C++
Java
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

none

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

yes

none

Multi-source replication
Source-replica replication

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

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

volatile and lookup table

yes

User concepts

Access control

simple password-based access control

Users with fine-grained authorization concept

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