DBMS > BoltDB vs. Postgres-XL vs. RocksDB vs. TimescaleDB vs. VoltDB

System Properties Comparison BoltDB vs. Postgres-XL vs. RocksDB vs. TimescaleDB vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

An embedded key-value store for Go.

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

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

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

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

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	0.74
Rank	#220	Overall
	#31	Key-value stores

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

github.com/boltdb/bolt

Technical documentation

www.postgres-xl.org/documentation

github.com/facebook/rocksdb/wiki

docs.timescale.com

docs.voltdb.com

Developer

Facebook, Inc.

Timescale

VoltDB Inc.

Initial release

2013

2014

since 2012, originally named StormDB

2013

2017

2010

Current release

10 R1, October 2018

8.11.4, April 2024

2.15.0, May 2024

11.3, April 2022

License

Commercial or Open Source

Open Source

MIT License

Open Source

Mozilla public license

Open Source

BSD

Open Source

Apache 2.0

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java, C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux
macOS

Linux

Linux
OS X
Windows

Linux
OS X

for development

Data scheme

schema-free

yes

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

SQL

Support of SQL

yes

distributed, parallel query execution

yes

full PostgreSQL SQL syntax

yes

only a subset of SQL 99

APIs and other access methods

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

C++ API
Java API

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

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

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

C
C++
Go
Java
Perl
Python
Ruby

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

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

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

yes, across time and space (hash partitioning) attributes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Source-replica replication with hot standby and reads on replicas

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

none

Immediate Consistency

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

yes

ACID

MVCC

yes

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

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

Users and roles with access to stored procedures

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