DBMS > Alibaba Cloud TSDB vs. GridGain vs. Heroic vs. Microsoft Azure Synapse Analytics

System Properties Comparison Alibaba Cloud TSDB vs. GridGain vs. Heroic vs. Microsoft Azure Synapse Analytics

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Editorial information provided by DB-Engines

Name

Description

A stable, reliable, and cost-effective online high-performance time series database service

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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

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

Primary database model

Time Series DBMS

Key-value store
Relational DBMS

Time Series DBMS

Relational DBMS

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

Score	0.29
Rank	#301	Overall
	#26	Time Series DBMS

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

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Website

www.alibabacloud.com/product/hitsdb

www.gridgain.com

github.com/spotify/heroic

azure.microsoft.com/services/synapse-analytics

Technical documentation

www.alibabacloud.com/help/en/time-series-database/latest/what-is-tsdb

www.gridgain.com/docs/index.html

spotify.github.io/heroic

docs.microsoft.com/azure/synapse-analytics

Developer

Alibaba

GridGain Systems, Inc.

Spotify

Microsoft

Initial release

2007

2014

2016

Current release

GridGain 8.5.1

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

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++, .Net

Java

C++

Server operating systems

hosted

Linux
OS X
Solaris
Windows

hosted

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

Numeric data and Strings

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

via Elasticsearch

yes

SQL

Support of SQL

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

yes

APIs and other access methods

HTTP REST

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

HQL (Heroic Query Language, a JSON-based language)
HTTP API

ADO.NET
JDBC
ODBC

Supported programming languages

Java

C#
C++
Java
PHP
Python
Ruby
Scala

C#
Java
PHP

Server-side scripts

Stored procedures

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

Transact SQL

Triggers

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

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
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

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

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

Access managed on TSDB instance level

Security Hooks for custom implementations

yes

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More resources

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