DBMS > BoltDB vs. LeanXcale vs. QuestDB vs. Sphinx vs. VoltDB

System Properties Comparison BoltDB vs. LeanXcale vs. QuestDB vs. Sphinx vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

An embedded key-value store for Go.

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

A high performance open source SQL database for time series data

Open source search engine for searching in data from different sources, e.g. relational databases

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

Key-value store

Key-value store
Relational DBMS

Time Series DBMS

Search engine

Relational DBMS

Secondary database models

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	0.29
Rank	#291	Overall
	#41	Key-value stores
	#132	Relational DBMS

Score	2.52
Rank	#109	Overall
	#9	Time Series DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

github.com/boltdb/bolt

Technical documentation

questdb.io/docs

sphinxsearch.com/docs

docs.voltdb.com

Developer

LeanXcale

QuestDB Technology Inc

Sphinx Technologies Inc.

VoltDB Inc.

Initial release

2013

2015

2014

2001

2010

Current release

3.5.1, February 2023

11.3, April 2022

License

Commercial or Open Source

Open Source

MIT License

commercial

Open Source

Apache 2.0

Open Source

GPL version 2, commercial licence available

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

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java (Zero-GC), C++, Rust

C++

Java, C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux
macOS
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Linux
OS X

for development

Data scheme

schema-free

yes

schema-free via InfluxDB Line Protocol

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.

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

yes

through Apache Derby

SQL with time-series extensions

SQL-like query language (SphinxQL)

yes

only a subset of SQL 99

APIs and other access methods

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol

Proprietary protocol

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

C
Java
Scala

PostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust

over HTTP

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

Java

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning (by timestamps)

Sharding

Partitioning is done manually, search queries against distributed index is supported

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication with eventual consistency

none

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

ACID for single-table writes

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

The original contents of fields are not stored in the Sphinx index.

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

through memory mapped files

User concepts

Access control

Users and roles with access to stored procedures

More information provided by the system vendor

Specific characteristics

Relational model with native time series support Column-based storage and time partitioned...
» more

Competitive advantages

High ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more

Typical application scenarios

Financial tick data Industrial IoT Application Metrics Monitoring
» more

Key customers

Banks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more

Licensing and pricing models

Open source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more

News

QuestDB and Raspberry Pi 5 benchmark, a pocket-sized powerhouse
8 May 2024

Build your own resource monitor with QuestDB and Grafana
6 May 2024

Does "vpmovzxbd" Scare You? Here's Why it Doesn't Have To
12 April 2024

Create an ADS-B flight radar with QuestDB and a Raspberry Pi
8 April 2024

Build a temperature IoT sensor with Raspberry Pi Pico & QuestDB
5 April 2024

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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More resources

DB-Engines blog posts

The DB-Engines ranking includes now search engines
4 February 2013, Paul Andlinger

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