DBMS > Firebird vs. GeoSpock vs. HarperDB vs. Microsoft SQL Server vs. Rockset

System Properties Comparison Firebird vs. GeoSpock vs. HarperDB vs. Microsoft SQL Server vs. Rockset

Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

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

Spatial and temporal data processing engine for extreme data scale

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

Microsofts flagship relational DBMS

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Primary database model

Secondary database models

Time Series DBMS

Document store
Graph DBMS
Spatial DBMS

Relational DBMS
Search engine

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

Score	20.50
Rank	#30	Overall
	#18	Relational DBMS

Score	0.60
Rank	#244	Overall
	#38	Document stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	0.82
Rank	#212	Overall
	#36	Document stores

Website

www.firebirdsql.org

geospock.com

www.harperdb.io

www.microsoft.com/en-us/sql-server

rockset.com

Technical documentation

www.firebirdsql.org/en/reference-manuals

docs.harperdb.io/docs

learn.microsoft.com/en-US/sql/sql-server

docs.rockset.com

Developer

Firebird Foundation

GeoSpock

HarperDB

Microsoft

Rockset

Initial release

2000

As fork of Borland's InterBase

2017

1989

2019

Current release

5.0.0, January 2024

2.0, September 2019

3.1, August 2021

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

Initial Developer's Public License

commercial

free community edition available

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

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Implementation language

C and C++

Java, Javascript

Node.js

C++

Server operating systems

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

hosted

Linux
OS X

Linux
Windows

hosted

Data scheme

yes

dynamic schema

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON data types

yes

dynamic typing

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

ingestion from XML files supported

Secondary indexes

yes

temporal, categorical

yes

all fields are automatically indexed

SQL

Support of SQL

yes

ANSI SQL for query only (using Presto)

SQL-like data manipulation statements

yes

Read-only SQL queries, including JOINs

APIs and other access methods

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

JDBC

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

HTTP REST

Supported programming languages

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

PSQL

Custom Functions

since release 3.1

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Automatic sharding

A table resides as a whole on one (or more) nodes in a cluster

tables can be distributed across several files (horizontal partitioning); sharding through federation

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

the nodes on which a table resides can be defined

yes, but depending on the SQL-Server Edition

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic execution of specific operations

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

yes, using LMDB

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

Users with fine-grained authorization concept

Access rights for users can be defined per table

Access rights for users and roles

fine grained access rights according to SQL-standard

Access rights for users and organizations can be defined via Rockset console

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