DBMS > Hazelcast vs. Manticore Search vs. Microsoft Azure Synapse Analytics vs. RocksDB vs. SAP Advantage Database Server

System Properties Comparison Hazelcast vs. Manticore Search vs. Microsoft Azure Synapse Analytics vs. RocksDB vs. SAP Advantage Database Server

Editorial information provided by DB-Engines

Name

SAP Advantage Database Server seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

A widely adopted in-memory data grid

Multi-storage database for search, including full-text search.

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Low-cost RDBMS with access to ISAM and FoxPro data structures

Primary database model

Secondary database models

Document store

JSON support with IMDG 3.12

Time Series DBMS

using the Manticore Columnar Library

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

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

Score	0.29
Rank	#302	Overall
	#21	Search engines

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

hazelcast.com

manticoresearch.com

azure.microsoft.com/services/synapse-analytics

rocksdb.org

www.sap.com/products/advantage-database-server.html

Technical documentation

hazelcast.org/imdg/docs

manual.manticoresearch.com

docs.microsoft.com/azure/synapse-analytics

github.com/facebook/rocksdb/wiki

Developer

Hazelcast

Manticore Software

Microsoft

Facebook, Inc.

Sybase, SAP

Initial release

2008

2017

2016

2013

1993

Current release

5.3.6, November 2023

6.0, February 2023

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

Open Source

GPL version 2

commercial

Open Source

BSD

commercial

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

Java

C++

Server operating systems

All OS with a Java VM

FreeBSD
Linux
macOS
Windows

hosted

Linux

Linux
Windows

Data scheme

schema-free

Fixed schema

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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

Can index from XML

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

JCache
JPA
Memcached protocol
RESTful HTTP API

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

ADO.NET
JDBC
ODBC

C++ API
Java API

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

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

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

C#
Java
PHP

C
C++
Go
Java
Perl
Python
Ruby

Delphi
Perl
PHP

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

user defined functions

Transact SQL

yes

Triggers

yes

Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Partitioning is done manually, search queries against distributed index is supported

Sharding, horizontal partitioning

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Replicated Map

Synchronous replication based on Galera library

yes

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
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

Foreign keys

Referential integrity

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

yes

Transaction concepts

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

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

yes

isolated transactions for atomic changes and binary logging for safe writes

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Manticore index.

yes

In-memory capabilities

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

yes

caching of (temporary) tables can be configured

User concepts

Access control

Role-based access control

yes

fine grained access rights according to SQL-standard

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