DBMS > BoltDB vs. Heroic vs. RocksDB vs. STSdb vs. TimescaleDB

System Properties Comparison BoltDB vs. Heroic vs. RocksDB vs. STSdb vs. TimescaleDB

Editorial information provided by DB-Engines

Name

Description

An embedded key-value store for Go.

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

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

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

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

Primary database model

Secondary database models

Relational DBMS

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

Score	0.76
Rank	#224	Overall
	#32	Key-value stores

Score	0.57
Rank	#250	Overall
	#21	Time Series DBMS

Score	4.00
Rank	#84	Overall
	#11	Key-value stores

Score	0.06
Rank	#365	Overall
	#55	Key-value stores

Score	4.87
Rank	#74	Overall
	#4	Time Series DBMS

Website

github.com/boltdb/bolt

github.com/spotify/heroic

rocksdb.org

github.com/STSSoft/STSdb4

www.timescale.com

Technical documentation

spotify.github.io/heroic

github.com/facebook/rocksdb/wiki

docs.timescale.com

Developer

Spotify

Facebook, Inc.

STS Soft SC

Timescale

Initial release

2013

2014

2013

2011

2017

Current release

8.11.4, April 2024

4.0.8, September 2015

2.13.0, November 2023

License

Commercial or Open Source

Open Source

MIT License

Open Source

Apache 2.0

Open Source

BSD

Open Source

GPLv2, commercial license available

Open Source

Apache 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

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux

Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

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

full PostgreSQL SQL syntax

APIs and other access methods

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

C++ API
Java API

.NET Client API

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

Supported programming languages

C
C++
Go
Java
Perl
Python
Ruby

C#
Java

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

none

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

none

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

User concepts

Access control

fine grained access rights according to SQL-standard

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