DBMS > Heroic vs. Postgres-XL vs. Riak KV vs. Tigris

System Properties Comparison Heroic vs. Postgres-XL vs. Riak KV vs. Tigris

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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

Distributed, fault tolerant key-value store

A horizontally scalable, ACID transactional, document database available both as a fully managed cloud service and for deployment on self-managed infrastructure

Primary database model

Time Series DBMS

Relational DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Document store
Key-value store
Search engine
Time Series DBMS

Secondary database models

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	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Score	0.09
Rank	#363	Overall
	#49	Document stores
	#54	Key-value stores
	#22	Search engines
	#38	Time Series DBMS

Website

github.com/spotify/heroic

www.postgres-xl.org

www.tigrisdata.com

Technical documentation

spotify.github.io/heroic

www.postgres-xl.org/documentation

www.tiot.jp/riak-docs/riak/kv/latest

www.tigrisdata.com/docs

Developer

Spotify

OpenSource, formerly Basho Technologies

Tigris Data, Inc.

Initial release

2014

since 2012, originally named StormDB

2009

2022

Current release

10 R1, October 2018

3.2.0, December 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Mozilla public license

Open Source

Apache version 2, commercial enterprise edition

Open Source

Apache Version 2.0

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

Erlang

Server operating systems

Linux
macOS

Linux
OS X

Linux
macOS
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

XML type, but no XML query functionality

Secondary indexes

yes

via Elasticsearch

yes

restricted

yes

SQL

Support of SQL

yes

distributed, parallel query execution

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

HTTP API
Native Erlang Interface

CLI Client
gRPC
RESTful HTTP API

Supported programming languages

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

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Go
Java
JavaScript (Node.js)

Server-side scripts

Stored procedures

user defined functions

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

no "single point of failure"

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

links between data sets can be stored

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

yes, using FoundationDB

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, using Riak Security

Access rights for users and roles

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