DBMS > GeoSpock vs. HarperDB vs. Microsoft SQL Server vs. RavenDB vs. Riak KV

System Properties Comparison GeoSpock vs. HarperDB vs. Microsoft SQL Server vs. RavenDB vs. Riak KV

Editorial information provided by DB-Engines

Name

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

Description

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

Open Source Operational and Transactional Enterprise NoSQL Document Database

Distributed, fault tolerant key-value store

Primary database model

with links between data sets and object tags for the creation of secondary indexes

Secondary database models

Time Series DBMS

Document store
Graph DBMS
Spatial DBMS

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.60
Rank	#244	Overall
	#38	Document stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	2.84
Rank	#101	Overall
	#18	Document stores

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Website

geospock.com

www.harperdb.io

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

ravendb.net

Technical documentation

docs.harperdb.io/docs

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

ravendb.net/docs

www.tiot.jp/riak-docs/riak/kv/latest

Developer

GeoSpock

HarperDB

Microsoft

Hibernating Rhinos

OpenSource, formerly Basho Technologies

Initial release

2017

1989

2010

2009

Current release

2.0, September 2019

3.1, August 2021

SQL Server 2022, November 2022

5.4, July 2022

3.2.0, December 2022

License

Commercial or Open Source

commercial

free community edition available

commercial

restricted free version is available

Open Source

AGPL version 3, commercial license available

Open Source

Apache version 2, commercial enterprise edition

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java, Javascript

Node.js

C++

Erlang

Server operating systems

hosted

Linux
OS X

Linux
Windows

Linux
macOS
Raspberry Pi
Windows

Linux
OS X

Data scheme

yes

dynamic schema

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

temporal, categorical

yes

restricted

SQL

Support of SQL

ANSI SQL for query only (using Presto)

SQL-like data manipulation statements

yes

SQL-like query language (RQL)

APIs and other access methods

JDBC

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

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

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

HTTP API
Native Erlang Interface

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

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

Custom Functions

since release 3.1

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

yes

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

yes

the nodes on which a table resides can be defined

yes, but depending on the SQL-Server Edition

Multi-source replication

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Eventual Consistency

Foreign keys

Referential integrity

yes

links between data sets can be stored

Transaction concepts

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

Atomic execution of specific operations

ACID

ACID, Cluster-wide transaction available

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

Access rights for users can be defined per table

Access rights for users and roles

fine grained access rights according to SQL-standard

Authorization levels configured per client per database

yes, using Riak Security

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