DBMS > Apache IoTDB vs. Bangdb vs. Derby vs. Oracle vs. SingleStore

System Properties Comparison Apache IoTDB vs. Bangdb vs. Derby vs. Oracle vs. SingleStore

Editorial information provided by DB-Engines

Name

Description

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

Converged and high performance database for device data, events, time series, document and graph

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Widely used RDBMS

MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type

Primary database model

Time Series DBMS

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

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

Score	1.31
Rank	#164	Overall
	#14	Time Series DBMS

Score	0.16
Rank	#338	Overall
	#47	Document stores
	#32	Graph DBMS
	#31	Time Series DBMS

Score	4.60
Rank	#70	Overall
	#38	Relational DBMS

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Score	5.38
Rank	#62	Overall
	#35	Relational DBMS

Website

iotdb.apache.org

bangdb.com

db.apache.org/derby

www.oracle.com/database

www.singlestore.com

Technical documentation

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

docs.bangdb.com

db.apache.org/derby/manuals/index.html

docs.oracle.com/en/database

docs.singlestore.com

Developer

Apache Software Foundation

Sachin Sinha, BangDB

Apache Software Foundation

Oracle

SingleStore Inc.

Initial release

2018

2012

1997

1980

2013

Current release

1.1.0, April 2023

BangDB 2.0, October 2021

10.17.1.0, November 2023

23c, September 2023

8.5, January 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

BSD 3

Open Source

Apache version 2

commercial

restricted free version is available

commercial

free developer edition 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.

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Implementation language

Java

C, C++

Java

C and C++

C++, Go

Server operating systems

All OS with a Java VM (>= 1.8)

Linux

All OS with a Java VM

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Linux

64 bit version required

Data scheme

yes

schema-free

yes

Schemaless in JSON and XML columns

yes

Typing

predefined data types such as float or date

yes

yes: string, long, double, int, geospatial, stream, events

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

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL-like query language

SQL like support with command line tool

yes

with proprietary extensions

yes

but no triggers and foreign keys

APIs and other access methods

JDBC
Native API

Proprietary protocol
RESTful HTTP API

JDBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

C
C#
C++
Java
Python

Java

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

Bash
C
C#
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Java Stored Procedures

PL/SQL

also stored procedures in Java possible

yes

Triggers

yes

yes, Notifications (with Streaming only)

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

none

Sharding, horizontal partitioning

Sharding

hash partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

selectable replication factor, Knob for CAP (enterprise version only)

Source-replica replication

Multi-source replication
Source-replica replication

Source-replica replication

stores two copies of each physical data partition on two separate nodes

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

can be realized in PL/SQL

can define user-defined aggregate functions for map-reduce-style calculations

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

isolation level can be parameterized

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

yes, implements WAL (Write ahead log) as well

yes

All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.

In-memory capabilities

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

yes

yes, run db with in-memory only mode

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

yes

User concepts

Access control

yes

yes (enterprise version only)

fine grained access rights according to SQL-standard

Fine grained access control via users, groups and roles

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Licensing and pricing models

F ree Tier and Enterprise Edition
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