DBMS > Hazelcast vs. MaxDB vs. Spark SQL vs. TimesTen

System Properties Comparison Hazelcast vs. MaxDB vs. Spark SQL vs. TimesTen

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Editorial information provided by DB-Engines

Name

Description

A widely adopted in-memory data grid

A robust and reliable RDBMS optimized to run all major SAP solutions

Spark SQL is a component on top of 'Spark Core' for structured data processing

In-Memory RDBMS compatible to Oracle

Primary database model

Key-value store

Relational DBMS

Secondary database models

Document store

JSON support with IMDG 3.12

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

Score	5.46
Rank	#61	Overall
	#7	Key-value stores

Score	2.26
Rank	#114	Overall
	#55	Relational DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Website

hazelcast.com

maxdb.sap.com

spark.apache.org/sql

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

Technical documentation

hazelcast.org/imdg/docs

maxdb.sap.com/documentation

spark.apache.org/docs/latest/sql-programming-guide.html

docs.oracle.com/database/timesten-18.1

Developer

Hazelcast

SAP, acquired from Software AG (Adabas-D) in 1997

Apache Software Foundation

Oracle, TimesTen Performance Software, HP

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

Initial release

2008

1984

2014

1998

Current release

5.3.6, November 2023

7.9.10.12, February 2024

3.5.0 ( 2.13), September 2023

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

commercial

Limited community edition free

Open Source

Apache 2.0

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

Java

C++

Scala

Server operating systems

All OS with a Java VM

AIX
HP-UX
Linux
Solaris
Windows

Linux
OS X
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

schema-free

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

the object must implement a serialization strategy

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

SQL-like DML and DDL statements

yes

APIs and other access methods

JCache
JPA
Memcached protocol
RESTful HTTP API

ADO.NET
JDBC
ODBC
WebDAV

JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

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

.Net
C#
Java
Perl
PHP
Python

Java
Python
R
Scala

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

yes

PL/SQL

Triggers

yes

Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes, utilizing Spark Core

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Replicated Map

Source-replica replication

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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

Durability

Support for making data persistent

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

Role-based access control

fine grained access rights according to SQL-standard

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