DBMS > GridGain vs. KairosDB vs. Microsoft Azure Synapse Analytics vs. SAP HANA

System Properties Comparison GridGain vs. KairosDB vs. Microsoft Azure Synapse Analytics vs. SAP HANA

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Editorial information provided by DB-Engines

Name

Description

GridGain is an in-memory computing platform, built on Apache Ignite

Distributed Time Series DBMS based on Cassandra or H2

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

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Key-value store
Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	1.55
Rank	#150	Overall
	#26	Key-value stores
	#70	Relational DBMS

Score	0.67
Rank	#233	Overall
	#20	Time Series DBMS

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

www.gridgain.com

github.com/kairosdb/kairosdb

azure.microsoft.com/services/synapse-analytics

www.sap.com/products/hana.html

Technical documentation

www.gridgain.com/docs/index.html

kairosdb.github.io

docs.microsoft.com/azure/synapse-analytics

help.sap.com/hana

Developer

GridGain Systems, Inc.

Microsoft

SAP

Initial release

2007

2013

2016

2010

Current release

GridGain 8.5.1

1.2.2, November 2018

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java, C++, .Net

Java

C++

Server operating systems

Linux
OS X
Solaris
Windows

Linux
OS X
Windows

hosted

Appliance or cloud-service

Data scheme

yes

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

Secondary indexes

yes

SQL

Support of SQL

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

yes

APIs and other access methods

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

Graphite protocol
HTTP REST
Telnet API

ADO.NET
JDBC
ODBC

JDBC
ODBC

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

Java
JavaScript

Node.js
PHP
Python

C#
Java
PHP

Server-side scripts

Stored procedures

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

Transact SQL

SQLScript, R

Triggers

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding, horizontal partitioning

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

selectable replication factor

based on Cassandra

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

ACID

Concurrency

Support for concurrent manipulation of data

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

Security Hooks for custom implementations

simple password-based access control

yes

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