DBMS > Apache Phoenix vs. Firebird vs. JSqlDb vs. Microsoft Azure Synapse Analytics vs. TimescaleDB

System Properties Comparison Apache Phoenix vs. Firebird vs. JSqlDb vs. Microsoft Azure Synapse Analytics vs. TimescaleDB

Editorial information provided by DB-Engines

Name

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

Description

A scale-out RDBMS with evolutionary schema built on Apache HBase

Firebird is an open source RDBMS forked from Borland's InterBase

JavaScript Query Language Database, stores JavaScript objects and primitives

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

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Relational DBMS

Document store
Object oriented DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	20.82
Rank	#30	Overall
	#18	Relational DBMS

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Website

phoenix.apache.org

www.firebirdsql.org

jsqldb.org (offline)

azure.microsoft.com/services/synapse-analytics

www.timescale.com

Technical documentation

phoenix.apache.org

www.firebirdsql.org/en/reference-manuals

docs.microsoft.com/azure/synapse-analytics

docs.timescale.com

Developer

Apache Software Foundation

Firebird Foundation

Konrad von Backstrom

Microsoft

Timescale

Initial release

2014

2000

As fork of Borland's InterBase

2018

2016

2017

Current release

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

5.0.0, January 2024

0.8, December 2018

2.13.0, November 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Initial Developer's Public License

Open Source

commercial

Open Source

Apache 2.0

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 and C++

C++

Server operating systems

Linux
Unix
Windows

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

Linux
macOS
Windows

hosted

Linux
OS X
Windows

Data scheme

yes

late-bound, schema-on-read capabilities

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

yes

full PostgreSQL SQL syntax

APIs and other access methods

JDBC

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

JavaScript

C#
Java
PHP

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

user defined functions

PSQL

functions in JavaScript

Transact SQL

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding, horizontal partitioning

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication

none

yes

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

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

Features a multi-generational MVCC architecture, readers do not block writers

yes

Durability

Support for making data persistent

yes

using RocksDB

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 Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

Users with fine-grained authorization concept

yes

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

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11 August 2021, Krishna Maheshwari (sponsor)

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