DBMS > Apache Impala vs. HarperDB vs. Memgraph vs. Microsoft SQL Server vs. Yanza

System Properties Comparison Apache Impala vs. HarperDB vs. Memgraph vs. Microsoft SQL Server vs. Yanza

Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Analytic DBMS for Hadoop

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.

An open source graph database built for real-time streaming and compatible with Neo4j

Microsofts flagship relational DBMS

Time Series DBMS for IoT Applications

Primary database model

Secondary database models

Document store

Document store
Graph DBMS
Spatial DBMS

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	0.55
Rank	#248	Overall
	#38	Document stores

Score	3.02
Rank	#98	Overall
	#8	Graph DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Website

impala.apache.org

www.harperdb.io

memgraph.com

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

yanza.com

Technical documentation

impala.apache.org/impala-docs.html

docs.harperdb.io/docs

memgraph.com/docs

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

Social network pages

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

HarperDB

Memgraph Ltd

Microsoft

Yanza

Initial release

2013

2017

1989

2015

Current release

4.1.0, June 2022

3.1, August 2021

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

free community edition available

Open Source

BSL 1.1; commercial license for enterprise edition available

commercial

restricted free version is available

commercial

free version available

Cloud-based only

Only available as a cloud service

but mainly used as a service provided by Yanza

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Implementation language

C++

Node.js

C and C++

C++

Server operating systems

Linux

Linux
OS X

Linux

Linux
Windows

Windows

Data scheme

yes

dynamic schema

schema-free and schema-optional

yes

schema-free

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

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like data manipulation statements

yes

APIs and other access methods

JDBC
ODBC

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

Bolt protocol
Cypher query language

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

HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

.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

.Net
C
C++
Elixir
Go
Haskell
Java
JavaScript
PHP
Python
Ruby
Scala

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

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Custom Functions

since release 3.1

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

Triggers

yes

Timer and event based

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

Sharding

dynamic graph partitioning

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

the nodes on which a table resides can be defined

Multi-source replication using RAFT

yes, but depending on the SQL-Server Edition

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

relationships in graphs

yes

Transaction concepts

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

Atomic execution of specific operations

ACID

with snapshot isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

yes, using LMDB

yes

with periodic snapshot and write-ahead logging (WAL) of changes

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, groups and roles

based on Apache Sentry and Kerberos

Access rights for users and roles

Users, roles and permissions

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

Graph algorithms in bioinformatics Social network analysis Cryptocurrency network...
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Licensing and pricing models

You can check out our pricing model and licenses on the company website .
» more

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