DBMS > Axibase vs. dBASE vs. HEAVY.AI vs. Microsoft SQL Server vs. Rockset

System Properties Comparison Axibase vs. dBASE vs. HEAVY.AI vs. Microsoft SQL Server vs. Rockset

Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

dBase was one of the first databases with a development environment on PC's. Its latest version dBase V is still sold as dBase classic, which needs a DOS Emulation. The up-to-date product is dBase plus.

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

Microsofts flagship relational DBMS

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

Primary database model

Time Series DBMS

Relational DBMS

Document store

Secondary database models

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

Relational DBMS
Search engine

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

Score	0.32
Rank	#288	Overall
	#25	Time Series DBMS

Score	11.18
Rank	#44	Overall
	#28	Relational DBMS

Score	2.10
Rank	#126	Overall
	#61	Relational DBMS

Score	829.80
Rank	#3	Overall
	#3	Relational DBMS

Score	0.84
Rank	#209	Overall
	#35	Document stores

Website

axibase.com/docs/atsd/finance

www.dbase.com

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

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

rockset.com

Technical documentation

www.dbase.com/support/knowledgebase

docs.heavy.ai

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

docs.rockset.com

Developer

Axibase Corporation

Asthon Tate

HEAVY.AI, Inc.

Microsoft

Rockset

Initial release

2013

1979

2016

1989

2019

Current release

15585

dBASE 2019, 2019

5.10, January 2022

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

commercial

Open Source

Apache Version 2; enterprise edition available

commercial

restricted free version is available

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++ and CUDA

C++

Server operating systems

Linux

DOS

dBase Classic
Windows

dBase Pro

Linux

Linux
Windows

hosted

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

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

all fields are automatically indexed

SQL

Support of SQL

SQL-like query language

yes

Read-only SQL queries, including JOINs

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

none

The IDE can access other DBMS or ODBC-sources.

JDBC
ODBC
Thrift
Vega

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

HTTP REST

Supported programming languages

Go
Java
PHP
Python
R
Ruby

dBase proprietary IDE

All languages supporting JDBC/ODBC/Thrift
Python

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

yes

The IDE can access stored procedures in other database systems.

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Round robin

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

none

Multi-source replication

yes, but depending on the SQL-Server Edition

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

not for dBase internal data, but IDE does support transactions when accessing external DBMS

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 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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