DBMS > ITTIA vs. Oracle Berkeley DB vs. QuestDB vs. SQLite

System Properties Comparison ITTIA vs. Oracle Berkeley DB vs. QuestDB vs. SQLite

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Editorial information provided by DB-Engines

Name

Description

Edge Time Series DBMS with Real-Time Stream Processing

Widely used in-process key-value store

A high performance open source SQL database for time series data

Widely used embeddable, in-process RDBMS

Primary database model

Time Series DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Time Series DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	0.39
Rank	#273	Overall
	#24	Time Series DBMS

Score	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Score	2.52
Rank	#109	Overall
	#9	Time Series DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

www.ittia.com

www.oracle.com/database/technologies/related/berkeleydb.html

questdb.io

www.sqlite.org

Technical documentation

docs.oracle.com/cd/E17076_05/html/index.html

questdb.io/docs

www.sqlite.org/docs.html

Developer

ITTIA L.L.C.

Oracle

originally developed by Sleepycat, which was acquired by Oracle

QuestDB Technology Inc

Dwayne Richard Hipp

Initial release

2007

1994

2014

2000

Current release

8.7

18.1.40, May 2020

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

commercial

Open Source

commercial license available

Open Source

Apache 2.0

Open Source

Public Domain

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 and C++

C, Java, C++ (depending on the Berkeley DB edition)

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

Server operating systems

Linux
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux
macOS
Windows

server-less

Data scheme

Fixed schema

schema-free

yes

schema-free via InfluxDB Line Protocol

yes

dynamic column types

Typing

predefined data types such as float or date

Float/Blob/Integer/String/Unicode/Date/Time/Timestamp/Interval

yes

not rigid because of 'dynamic typing' concept.

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

only with the Berkeley DB XML edition

Secondary indexes

yes

SQL

Support of SQL

yes

SQL interfaced based on SQLite is available

SQL with time-series extensions

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC
ODBC
RESTful HTTP API
WebSocket

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

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

C
C++
JavaScript (Node.js)
Python

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

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

over HTTP

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

Triggers

yes

only for the SQL API

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning (by timestamps)

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

Source-replica replication with eventual consistency

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

ACID for single-table writes

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

via file-system locks

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

through memory mapped files

yes

User concepts

Access control

Database file passwords

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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