DBMS > BigchainDB vs. ITTIA vs. Postgres-XL vs. Splice Machine

System Properties Comparison BigchainDB vs. ITTIA vs. Postgres-XL vs. Splice Machine

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

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

Edge Time Series DBMS with Real-Time Stream Processing

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

Document store

Time Series DBMS

Relational DBMS

Secondary database models

Relational DBMS

Document store
Spatial DBMS

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

Score	0.76
Rank	#216	Overall
	#36	Document stores

Score	0.36
Rank	#272	Overall
	#22	Time Series DBMS

Score	0.43
Rank	#260	Overall
	#119	Relational DBMS

Score	0.54
Rank	#244	Overall
	#114	Relational DBMS

Website

Technical documentation

bigchaindb.readthedocs.io/en/latest

www.postgres-xl.org/documentation

splicemachine.com/how-it-works

Developer

ITTIA L.L.C.

Splice Machine

Initial release

2016

2007

2014

since 2012, originally named StormDB

2014

Current release

8.7

10 R1, October 2018

3.1, March 2021

License

Commercial or Open Source

Open Source

AGPL v3

commercial

Open Source

Mozilla public license

Open Source

AGPL 3.0, commercial license 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

Python

C and C++

Java

Server operating systems

Linux

Linux
Windows

Linux
macOS

Linux
OS X
Solaris
Windows

Data scheme

schema-free

Fixed schema

yes

Typing

predefined data types such as float or date

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

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

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

distributed, parallel query execution

yes

APIs and other access methods

CLI Client
RESTful HTTP API

JDBC
ODBC
RESTful HTTP API
WebSocket

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

JDBC
Native Spark Datasource
ODBC

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

C
C++
JavaScript (Node.js)
Python

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

yes

user defined functions

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

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

MVCC

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes,with MongoDB ord RethinkDB

yes

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

Database file passwords

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Using BigchainDB: A Database with Blockchain Characteristics
20 January 2022, Open Source For You

Top 10 startups in Digital Twin in Germany
11 July 2024, Tracxn

7 blockchain firms join Bosch led GAIA-X consortium for vehicle identity
13 September 2022, Ledger Insights

BigchainDB: A Popular and Powerful Database for Blockchain
9 September 2019, Open Source For You

How to use blockchain to build a database solution
2 March 2017, ZDNet

provided by Google News

Embedded secured data base for STM32 MCUs
16 October 2023, Electronics Weekly

provided by Google News

Machine learning data pipeline outfit Splice Machine files for insolvency
26 August 2021, The Register

Splice Machine Launches the Splice Machine Feature Store to Simplify Feature Engineering and Democratize Machine Learning
19 January 2021, PR Newswire

2021: The Year of the Feature Store
19 January 2021, Datanami

Monte Zweben's Splice Machine Introduces New Hadoop RDBMS
24 June 2014, Forbes

Splice Machine Launches ML Manager Beta Program to Meet the Growing Demand for Operational AI
7 April 2019, insideBIGDATA

provided by Google News

Share this page