DBMS > atoti vs. BigchainDB vs. InfinityDB vs. Microsoft SQL Server vs. TimesTen

System Properties Comparison atoti vs. BigchainDB vs. InfinityDB vs. Microsoft SQL Server 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.

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

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

Microsofts flagship relational DBMS

In-Memory RDBMS compatible to Oracle

Primary database model

Secondary database models

Document store
Graph DBMS
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	0.79
Rank	#212	Overall
	#36	Document stores

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

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

atoti.io

www.bigchaindb.com

boilerbay.com

www.microsoft.com/en-us/sql-server

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

Technical documentation

docs.atoti.io

bigchaindb.readthedocs.io/en/latest

boilerbay.com/infinitydb/manual

learn.microsoft.com/en-US/sql/sql-server

docs.oracle.com/database/timesten-18.1

Developer

ActiveViam

Boiler Bay Inc.

Microsoft

Oracle, TimesTen Performance Software, HP

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

Initial release

2016

2002

1989

1998

Current release

4.0

SQL Server 2022, November 2022

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

free versions available

Open Source

AGPL v3

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

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Implementation language

Java

Python

Java

C++

Server operating systems

Linux

All OS with a Java VM

Linux
Windows

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

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.

yes

Secondary indexes

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

yes

SQL

Support of SQL

Multidimensional Expressions (MDX)

yes

APIs and other access methods

CLI Client
RESTful HTTP API

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

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

Java

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

Python

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding

none

tables can be distributed across several files (horizontal partitioning); sharding through federation

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

yes, but depending on the SQL-Server Edition

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

Immediate Consistency

READ-COMMITTED or SERIALIZED

Immediate Consistency

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

Durability

Support for making data persistent

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

User concepts

Access control

yes

fine grained access rights according to SQL-standard

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