DBMS > BigObject vs. HarperDB vs. Microsoft SQL Server vs. SAP HANA vs. Teradata Aster

System Properties Comparison BigObject vs. HarperDB vs. Microsoft SQL Server vs. SAP HANA vs. Teradata Aster

Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

Analytic DBMS for real-time computations and queries

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

In-memory, column based data store. Available as appliance or cloud service

Platform for big data analytics on multistructured data sources and types

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Document store

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	0.55
Rank	#248	Overall
	#38	Document stores

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

bigobject.io

www.harperdb.io

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

www.sap.com/products/hana.html

Technical documentation

docs.bigobject.io

docs.harperdb.io/docs

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

help.sap.com/hana

Developer

BigObject, Inc.

HarperDB

Microsoft

SAP

Teradata

Initial release

2015

2017

1989

2010

2005

Current release

3.1, August 2021

SQL Server 2022, November 2022

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

free community edition available

commercial

free community edition available

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

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Implementation language

Node.js

C++

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux
OS X

Linux
Windows

Appliance or cloud-service

Linux

Data scheme

yes

dynamic schema

yes

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

Typing

predefined data types such as float or date

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

in Aster File Store

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like data manipulation statements

yes

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

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

JDBC
ODBC

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

.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

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

Lua

Custom Functions

since release 3.1

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

SQLScript, R

R packages

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

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

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

the nodes on which a table resides can be defined

yes, but depending on the SQL-Server Edition

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

Access rights for users and roles

fine grained access rights according to SQL-standard

yes

fine grained access rights according to SQL-standard

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