DBMS > HEAVY.AI vs. JSqlDb vs. Microsoft Azure Synapse Analytics vs. SiteWhere vs. Tarantool

System Properties Comparison HEAVY.AI vs. JSqlDb vs. Microsoft Azure Synapse Analytics vs. SiteWhere vs. Tarantool

Editorial information provided by DB-Engines

Name

JSqlDB seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

JavaScript Query Language Database, stores JavaScript objects and primitives

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

M2M integration platform for persisting/querying time series data

In-memory computing platform with a flexible data schema for efficiently building high-performance applications

Primary database model

Relational DBMS

Document store
Object oriented DBMS

Relational DBMS

Time Series DBMS

Document store
Key-value store
Relational DBMS

Secondary database models

Spatial DBMS

with Tarantool/GIS extension

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

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	0.06
Rank	#383	Overall
	#43	Time Series DBMS

Score	1.67
Rank	#143	Overall
	#25	Document stores
	#25	Key-value stores
	#65	Relational DBMS

Website

github.com/heavyai/heavydb
www.heavy.ai

jsqldb.org (offline)

azure.microsoft.com/services/synapse-analytics

github.com/sitewhere/sitewhere

www.tarantool.io

Technical documentation

docs.heavy.ai

docs.microsoft.com/azure/synapse-analytics

sitewhere1.sitewhere.io/index.html

www.tarantool.io/en/doc

Developer

HEAVY.AI, Inc.

Konrad von Backstrom

Microsoft

SiteWhere

Initial release

2016

2018

2016

2010

2008

Current release

5.10, January 2022

0.8, December 2018

2.10.0, May 2022

License

Commercial or Open Source

Open Source

Apache Version 2; enterprise edition available

Open Source

commercial

Open Source

Common Public Attribution License Version 1.0

Open Source

BSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise

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

C++ and CUDA

C++

Java

C and C++

Server operating systems

Linux

Linux
macOS
Windows

hosted

Linux
OS X
Windows

BSD
Linux
macOS

Data scheme

yes

schema-free

yes

predefined scheme

Flexible data schema: relational definition for tables with ability to store json-like documents in columns

Typing

predefined data types such as float or date

yes

string, double, decimal, uuid, integer, blob, boolean, datetime

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.

Secondary indexes

yes

SQL

Support of SQL

yes

Full-featured ANSI SQL support

APIs and other access methods

JDBC
ODBC
Thrift
Vega

ADO.NET
JDBC
ODBC

HTTP REST

Open binary protocol

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

JavaScript

C#
Java
PHP

C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust

Server-side scripts

Stored procedures

functions in JavaScript

Transact SQL

Lua, C and SQL stored procedures

Triggers

yes, before/after data modification events, on replication events, client session events

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

none

Sharding, horizontal partitioning

Sharding

based on HBase

Sharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

yes

selectable replication factor

based on HBase

Asynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Casual consistency across sharding partitions
Eventual consistency within replicaset partition

when using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition

when using Raft

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

ACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions

Concurrency

Support for concurrent manipulation of data

yes

yes, cooperative multitasking

Durability

Support for making data persistent

yes

using RocksDB

yes

yes, write ahead logging

In-memory capabilities

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

yes

yes, full featured in-memory storage engine with persistence

User concepts

Access control

fine grained access rights according to SQL-standard

yes

Users with fine-grained authorization concept

Access Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

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More resources

DB-Engines blog posts

Data processing speed and reliability: in-memory synchronous replication
9 November 2021, Vladimir Perepelytsya, Tarantool (sponsor)

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