DBMS > Hazelcast vs. LeanXcale vs. Splice Machine vs. SWC-DB

System Properties Comparison Hazelcast vs. LeanXcale vs. Splice Machine vs. SWC-DB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

A widely adopted in-memory data grid

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

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

A high performance, scalable Wide Column DBMS

Primary database model

Key-value store

Key-value store
Relational DBMS

Relational DBMS

Wide column store

Secondary database models

Document store

JSON support with IMDG 3.12

Time Series DBMS

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

Score	5.97
Rank	#57	Overall
	#6	Key-value stores

Score	0.29
Rank	#291	Overall
	#41	Key-value stores
	#132	Relational DBMS

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

hazelcast.com

www.leanxcale.com

splicemachine.com

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

hazelcast.org/imdg/docs

splicemachine.com/how-it-works

Developer

Hazelcast

LeanXcale

Splice Machine

Alex Kashirin

Initial release

2008

2015

2014

2020

Current release

5.3.6, November 2023

3.1, March 2021

0.5, April 2021

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

commercial

Open Source

AGPL 3.0, commercial license available

Open Source

GPL V3

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++

Server operating systems

All OS with a Java VM

Linux
OS X
Solaris
Windows

Linux

Data scheme

schema-free

yes

schema-free

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

the object must implement a serialization strategy

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

through Apache Derby

yes

SQL-like query language

APIs and other access methods

JCache
JPA
Memcached protocol
RESTful HTTP API

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

JDBC
Native Spark Datasource
ODBC

Proprietary protocol
Thrift

Supported programming languages

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

C
Java
Scala

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

C++

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

yes

Java

Triggers

yes

Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Shared Nothhing Auto-Sharding, Columnar Partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Replicated Map

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

one or two-phase-commit; repeatable reads; read commited

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

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

Role-based access control

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

Hazelcast Showcases Real-Time Data Platform at 2024 Gartner Summit
15 May 2024, Datanami

Hazelcast Weaves Wider Logic Threads Through The Data Fabric
7 March 2024, Forbes

Hazelcast 5.4 real time data processing platform boosts AI and consistency
17 April 2024, VentureBeat

Hazelcast Versus Redis: A Practical Comparison
4 January 2024, Database Trends and Applications

Hazelcast: The 'true' value of streaming real-time data
27 September 2023, ComputerWeekly.com

provided by Google News

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

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

New Splice Machine RDBMS unites OLTP and OLAP
18 November 2015, CIO

How To Axe Db2 But Keep Your Code
10 March 2020, Towards Data Science

Hadoop-based RDBMS Now Available from Splice
12 May 2014, Datanami

provided by Google News

2022 All O-Zone Football Team
17 December 2022, Ozarks Sports Zone

provided by Google News

Share this page