DBMS > Heroic vs. Postgres-XL vs. RocksDB vs. searchxml

System Properties Comparison Heroic vs. Postgres-XL vs. RocksDB vs. searchxml

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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

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

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Time Series DBMS

Relational DBMS

Key-value store

Native XML DBMS
Search engine

Secondary database models

Document store
Spatial DBMS

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

Score	0.13
Rank	#335	Overall
	#29	Time Series DBMS

Score	0.43
Rank	#260	Overall
	#119	Relational DBMS

Score	2.84
Rank	#97	Overall
	#16	Key-value stores

Score	0.00
Rank	#385	Overall
	#7	Native XML DBMS
	#24	Search engines

Website

github.com/spotify/heroic

www.postgres-xl.org

rocksdb.org

www.searchxml.net/category/products

Technical documentation

spotify.github.io/heroic

www.postgres-xl.org/documentation

github.com/facebook/rocksdb/wiki

www.searchxml.net/support/handouts

Developer

Spotify

Facebook, Inc.

informationpartners gmbh

Initial release

2014

since 2012, originally named StormDB

2013

2015

Current release

10 R1, October 2018

9.4.0, June 2024

1.0

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Mozilla public license

Open Source

BSD

commercial

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++

Server operating systems

Linux
macOS

Linux

Windows

Data scheme

schema-free

yes

schema-free

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

yes

Secondary indexes

yes

via Elasticsearch

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

C++ API
Java API

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

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

C
C++
Go
Java
Perl
Python
Ruby

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

user defined functions

yes

on the application server

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

sychronisation to multiple collections

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

yes

multiple readers, single writer

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

User concepts

Access control

fine grained access rights according to SQL-standard

Domain, group and role-based access control at the document level and for application services

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