DBMS > Heroic vs. PostGIS vs. RocksDB vs. TDSQL for MySQL vs. TimesTen

System Properties Comparison Heroic vs. PostGIS vs. RocksDB vs. TDSQL for MySQL vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

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

Spatial extension of PostgreSQL

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

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.

In-Memory RDBMS compatible to Oracle

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	21.72
Rank	#29	Overall
	#1	Spatial DBMS

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

Score	0.85
Rank	#207	Overall
	#97	Relational DBMS

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Website

github.com/spotify/heroic

postgis.net

rocksdb.org

www.tencentcloud.com/products/dcdb

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

spotify.github.io/heroic

postgis.net/documentation

github.com/facebook/rocksdb/wiki

www.tencentcloud.com/document/product/1042

docs.oracle.com/database/timesten-18.1

Developer

Spotify

Facebook, Inc.

Tencent

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2014

2005

2013

1998

Current release

3.4.2, February 2024

9.2.1, May 2024

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GPL v2.0

Open Source

BSD

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

hosted

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

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.

yes

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

yes

APIs and other access methods

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

C++ API
Java API

JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

C
C++
Go
Java
Perl
Python
Ruby

C
C#
C++
Java
PHP
Python
Ruby

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

user defined functions

yes

PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

based on PostgreSQL

horizontal partitioning

Automatic sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

based on PostgreSQL

yes

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

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

In-memory capabilities

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

yes

User concepts

Access control

yes

based on PostgreSQL

Users with fine-grained authorization concept

fine grained access rights according to SQL-standard

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