DBMS > Badger vs. LevelDB vs. QuestDB vs. RocksDB vs. Sphinx

System Properties Comparison Badger vs. LevelDB vs. QuestDB vs. RocksDB vs. Sphinx

Editorial information provided by DB-Engines

Name

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

A high performance open source SQL database for time series data

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

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

Primary database model

Secondary database models

Relational DBMS

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

Score	0.20
Rank	#325	Overall
	#49	Key-value stores

Score	2.75
Rank	#107	Overall
	#19	Key-value stores

Score	2.48
Rank	#115	Overall
	#9	Time Series DBMS

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

Score	6.03
Rank	#60	Overall
	#6	Search engines

Website

github.com/dgraph-io/badger

github.com/google/leveldb

questdb.io

rocksdb.org

sphinxsearch.com

Technical documentation

godoc.org/github.com/dgraph-io/badger

github.com/google/leveldb/blob/main/doc/index.md

questdb.io/docs

github.com/facebook/rocksdb/wiki

sphinxsearch.com/docs

Developer

DGraph Labs

Google

QuestDB Technology Inc

Facebook, Inc.

Sphinx Technologies Inc.

Initial release

2017

2011

2014

2013

2001

Current release

1.23, February 2021

8.11.4, April 2024

3.5.1, February 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

BSD

Open Source

Apache 2.0

Open Source

BSD

Open Source

GPL version 2, commercial licence available

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

C++

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

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Illumos
Linux
OS X
Windows

Linux
macOS
Windows

Linux

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

schema-free

yes

schema-free via InfluxDB Line Protocol

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.

Secondary indexes

yes

full-text index on all search fields

SQL

Support of SQL

SQL with time-series extensions

SQL-like query language (SphinxQL)

APIs and other access methods

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

C++ API
Java API

Proprietary protocol

Supported programming languages

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

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

over HTTP

C
C++
Go
Java
Perl
Python
Ruby

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning (by timestamps)

horizontal partitioning

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication with eventual consistency

yes

none

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

Transaction concepts

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

ACID for single-table writes

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

yes

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

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

through memory mapped files

yes

User concepts

Access control

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

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