DBMS > Heroic vs. Postgres-XL vs. TimescaleDB vs. WakandaDB

System Properties Comparison Heroic vs. Postgres-XL vs. TimescaleDB vs. WakandaDB

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Editorial information provided by DB-Engines

Name

Description

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

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Secondary database models

Document store
Spatial DBMS

Relational DBMS

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

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

github.com/spotify/heroic

www.postgres-xl.org

www.timescale.com

wakanda.github.io

Technical documentation

spotify.github.io/heroic

www.postgres-xl.org/documentation

docs.timescale.com

wakanda.github.io/doc

Developer

Spotify

Timescale

Wakanda SAS

Initial release

2014

since 2012, originally named StormDB

2017

2012

Current release

10 R1, October 2018

2.15.0, May 2024

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Mozilla public license

Open Source

Apache 2.0

Open Source

AGPLv3, extended commercial license available

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++, JavaScript

Server operating systems

Linux
macOS

Linux
OS X
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

XML type, but no XML query functionality

yes

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

yes

distributed, parallel query execution

yes

full PostgreSQL SQL syntax

APIs and other access methods

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

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

RESTful HTTP API

Supported programming languages

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

JavaScript

Server-side scripts

Stored procedures

user defined functions

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

yes, across time and space (hash partitioning) attributes

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication with hot standby and reads on replicas

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

MVCC

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.

User concepts

Access control

fine grained access rights according to SQL-standard

yes

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