DBMS > Bangdb vs. Microsoft Azure AI Search vs. Splice Machine

System Properties Comparison Bangdb vs. Microsoft Azure AI Search vs. Splice Machine

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

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

Search-as-a-service for web and mobile app development

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

Primary database model

Document store
Graph DBMS
Time Series DBMS

Search engine

Relational DBMS

Secondary database models

Spatial DBMS

Vector DBMS

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

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

Score	5.59
Rank	#63	Overall
	#7	Search engines

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Website

bangdb.com

azure.microsoft.com/en-us/services/search

splicemachine.com

Technical documentation

docs.bangdb.com

learn.microsoft.com/en-us/azure/search

splicemachine.com/how-it-works

Developer

Sachin Sinha, BangDB

Microsoft

Splice Machine

Initial release

2012

2015

2014

Current release

BangDB 2.0, October 2021

3.1, March 2021

License

Commercial or Open Source

Open Source

BSD 3

commercial

Open Source

AGPL 3.0, commercial license available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, C++

Java

Server operating systems

Linux

hosted

Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

RESTful HTTP API

JDBC
Native Spark Datasource
ODBC

Supported programming languages

C
C#
C++
Java
Python

C#
Java
JavaScript
Python

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

Server-side scripts

Stored procedures

yes

Java

Triggers

yes, Notifications (with Streaming only)

yes

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

Implicit feature of the cloud service

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes

Implicit feature of the cloud service

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

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

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

In-memory capabilities

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

yes, run db with in-memory only mode

yes

User concepts

Access control

yes (enterprise version only)

yes

using Azure authentication

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

Azure AI Studio Now Generally Available, Sporting New Models Both Big and Small
21 May 2024, Visual Studio Magazine

Announcing updates to Azure AI Search to help organizations build and scale generative AI applications
4 April 2024, azure.microsoft.com

Microsoft beefs up Azure's arsenal of generative AI development tools
21 May 2024, SiliconANGLE News

Microsoft Azure AI gains new LLMs, governance features
21 May 2024, InfoWorld

Microsoft Azure gets 'Models as a Service,' enhanced RAG offerings for enterprise generative AI
21 May 2024, ZDNet

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 ...
19 January 2021, PR Newswire

Splice Machine Launches Feature Store to Simplify Feature Engineering
19 January 2021, Datanami

How Splice Machine's Data Platform for Intelligent Apps Works
29 September 2020, eWeek

Distributed SQL System Review: Snowflake vs Splice Machine
18 September 2019, Towards Data Science

provided by Google News

Share this page