DBMS > BigObject vs. Ignite vs. Splice Machine vs. Ultipa

System Properties Comparison BigObject vs. Ignite vs. Splice Machine vs. Ultipa

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

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

High performance Graph DBMS supporting HTAP high availability cluster deployment

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Key-value store
Relational DBMS

Relational DBMS

Graph DBMS

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

Score	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	3.11
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Score	0.19
Rank	#330	Overall
	#30	Graph DBMS

Website

Technical documentation

docs.bigobject.io

apacheignite.readme.io/docs

splicemachine.com/how-it-works

www.ultipa.com/document

Developer

BigObject, Inc.

Apache Software Foundation

Splice Machine

Ultipa

Initial release

2015

2014

2019

Current release

Apache Ignite 2.6

3.1, March 2021

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache 2.0

Open Source

AGPL 3.0, commercial license available

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

C++, Java, .Net

Java

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux
OS X
Solaris
Windows

Data scheme

yes

Typing

predefined data types such as float or date

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

SQL

Support of SQL

SQL-like DML and DDL statements

ANSI-99 for query and DML statements, subset of DDL

yes

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

JDBC
Native Spark Datasource
ODBC

RESTful HTTP API

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

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

C++
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Lua

yes (compute grid and cache interceptors can be used instead)

yes

Java

Triggers

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes (replicated cache)

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

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

Security Hooks for custom implementations

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

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More resources

Recent citations in the news

GridGain Announces Call for Speakers for Virtual Apache Ignite Summit 2024
8 February 2024, PR Newswire

Apache Ignite: An Overview
6 September 2023, Open Source For You

GridGain Unified Real-Time Data Platform Version 8.9 Addresses Today's More Complex Real-Time Data Processing ...
12 October 2023, GlobeNewswire

What is Apache Ignite? How is Apache Ignite Used?
18 July 2022, The Stack

Real-time in-memory OLTP and Analytics with Apache Ignite on AWS | Amazon Web Services
14 May 2016, AWS Blog

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

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

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

Splice Machine scores $15M to make Hadoop run in real time
10 February 2014, VentureBeat

provided by Google News

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