DBMS > atoti vs. Bangdb vs. BigchainDB vs. InfinityDB vs. TimesTen

System Properties Comparison atoti vs. Bangdb vs. BigchainDB vs. InfinityDB vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

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

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

A Java embedded Key-Value Store which extends the Java Map interface

In-Memory RDBMS compatible to Oracle

Primary database model

Object oriented DBMS

Document store
Graph DBMS
Time Series DBMS

Document store

Key-value store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	0.00
Rank	#378	Overall
	#57	Key-value stores

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

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

Technical documentation

docs.atoti.io

docs.bangdb.com

bigchaindb.readthedocs.io/en/latest

boilerbay.com/infinitydb/manual

docs.oracle.com/database/timesten-18.1

Developer

ActiveViam

Sachin Sinha, BangDB

Boiler Bay Inc.

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2012

2016

2002

1998

Current release

BangDB 2.0, October 2021

4.0

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

free versions available

Open Source

BSD 3

Open Source

AGPL v3

commercial

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

C, C++

Python

Java

Server operating systems

Linux

All OS with a Java VM

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

schema-free

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

yes

Typing

predefined data types such as float or date

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

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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

secondary, composite, nested, reverse, geospatial

manual creation possible, using inversions based on multi-value capability

yes

SQL

Support of SQL

Multidimensional Expressions (MDX)

SQL like support with command line tool

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

CLI Client
RESTful HTTP API

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

C
C#
C++
Java
Python

Go
Haskell
Java
JavaScript
Python
Ruby

Java

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

Python

PL/SQL

Triggers

yes, Notifications (with Streaming only)

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

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

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

selectable replication factor

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

Tunable consistency, set CAP knob accordingly

Immediate Consistency

READ-COMMITTED or SERIALIZED

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

manual creation possible, using inversions based on multi-value capability

yes

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes,with MongoDB ord RethinkDB

yes

by means of logfiles and checkpoints

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

User concepts

Access control

yes (enterprise version only)

yes

fine grained access rights according to SQL-standard

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