DBMS > Altibase vs. Axibase vs. HarperDB vs. HugeGraph vs. Microsoft SQL Server

System Properties Comparison Altibase vs. Axibase vs. HarperDB vs. HugeGraph vs. Microsoft SQL Server

Editorial information provided by DB-Engines

Name

Description

An enterprise grade, high-performance RDBMS

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

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.

A fast-speed and highly-scalable Graph DBMS

Microsofts flagship relational DBMS

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	1.07
Rank	#186	Overall
	#87	Relational DBMS

Score	0.29
Rank	#292	Overall
	#25	Time Series DBMS

Score	0.55
Rank	#248	Overall
	#38	Document stores

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Website

altibase.com

axibase.com/docs/atsd/finance

www.harperdb.io

github.com/hugegraph
hugegraph.apache.org

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

Technical documentation

github.com/ALTIBASE/Documents/tree/master/Manuals

docs.harperdb.io/docs

hugegraph.apache.org/docs

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

Developer

Altibase

Axibase Corporation

HarperDB

Baidu

Microsoft

Initial release

1999

2013

2017

2018

1989

Current release

v7.3, 2023, August 2023

15585

3.1, August 2021

0.9

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

commercial

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

commercial

free community edition available

Open Source

Apache Version 2.0

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

Node.js

Java

C++

Server operating systems

AIX
HP-UX
Linux

Linux

Linux
OS X

Linux
macOS
Unix

Linux
Windows

Data scheme

yes

dynamic schema

yes

Typing

predefined data types such as float or date

yes

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

yes

JSON data types

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

also supports composite index and range index

yes

SQL

Support of SQL

ANSI SQL-92

SQL-like query language

SQL-like data manipulation statements

yes

APIs and other access methods

JDBC
ODBC
Proprietary protocol

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

Java API
RESTful HTTP API
TinkerPop Gremlin

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

Supported programming languages

C
C++
Java

Go
Java
PHP
Python
R
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

Groovy
Java
Python

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

Server-side scripts

Stored procedures

stored procedures and stored functions

yes

Custom Functions

since release 3.1

asynchronous Gremlin script jobs

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

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

yes

depending on used storage backend, e.g. Cassandra and HBase

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes

the nodes on which a table resides can be defined

yes

depending on used storage backend, e.g. Cassandra and HBase

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

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

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

fine grained access rights according to SQL-standard

Access rights for users and roles

Users, roles and permissions

fine grained access rights according to SQL-standard

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