DBMS > GeoSpock vs. HarperDB vs. InfinityDB vs. Memcached vs. Microsoft SQL Server

System Properties Comparison GeoSpock vs. HarperDB vs. InfinityDB vs. Memcached vs. Microsoft SQL Server

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.

A Java embedded Key-Value Store which extends the Java Map interface

In-memory key-value store, originally intended for caching

Microsofts flagship relational DBMS

Primary database model

Secondary database models

Time Series DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	0.55
Rank	#248	Overall
	#38	Document stores

Score	0.00
Rank	#378	Overall
	#57	Key-value stores

Score	19.42
Rank	#32	Overall
	#4	Key-value stores

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Website

geospock.com

www.harperdb.io

boilerbay.com

www.memcached.org

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

Technical documentation

docs.harperdb.io/docs

boilerbay.com/infinitydb/manual

github.com/memcached/memcached/wiki

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

Developer

GeoSpock

HarperDB

Boiler Bay Inc.

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Microsoft

Initial release

2017

2002

2003

1989

Current release

2.0, September 2019

3.1, August 2021

4.0

1.6.25, March 2024

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

free community edition available

commercial

Open Source

BSD license

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

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Implementation language

Java, Javascript

Node.js

Java

C++

Server operating systems

hosted

Linux
OS X

All OS with a Java VM

FreeBSD
Linux
OS X
Unix
Windows

Linux
Windows

Data scheme

yes

dynamic schema

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON data types

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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

manual creation possible, using inversions based on multi-value capability

yes

SQL

Support of SQL

ANSI SQL for query only (using Presto)

SQL-like data manipulation statements

yes

APIs and other access methods

JDBC

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

Proprietary protocol

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

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

Java

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

Custom Functions

since release 3.1

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

Triggers

yes

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

none

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes

the nodes on which a table resides can be defined

none

Repcached, a Memcached patch, provides this functionallity

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

READ-COMMITTED or SERIALIZED

Immediate Consistency

Foreign keys

Referential integrity

manual creation possible, using inversions based on multi-value capability

yes

Transaction concepts

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

Atomic execution of specific operations

ACID

Optimistic locking for transactions; no isolation for bulk loads

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

Access rights for users can be defined per table

Access rights for users and roles

yes

using SASL (Simple Authentication and Security Layer) protocol

fine grained access rights according to SQL-standard

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