DBMS > Cachelot.io vs. Lovefield vs. SAP Advantage Database Server vs. Splice Machine vs. Stardog

System Properties Comparison Cachelot.io vs. Lovefield vs. SAP Advantage Database Server vs. Splice Machine vs. Stardog

Editorial information provided by DB-Engines

Name

SAP Advantage Database Server seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

In-memory caching system

Embeddable relational database for web apps written in pure JavaScript

Low-cost RDBMS with access to ISAM and FoxPro data structures

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

Key-value store

Relational DBMS

Graph DBMS
RDF store

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

Score	0.04
Rank	#388	Overall
	#62	Key-value stores

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Score	2.07
Rank	#122	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

cachelot.io

google.github.io/lovefield

www.sap.com/products/advantage-database-server.html

splicemachine.com

www.stardog.com

Technical documentation

github.com/google/lovefield/blob/master/docs/spec_index.md

splicemachine.com/how-it-works

docs.stardog.com

Developer

Google

Sybase, SAP

Splice Machine

Stardog-Union

Initial release

2015

2014

1993

2014

2010

Current release

2.1.12, February 2017

3.1, March 2021

7.3.0, May 2020

License

Commercial or Open Source

Open Source

Simplified BSD License

Open Source

Apache 2.0

commercial

Open Source

AGPL 3.0, commercial license available

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

JavaScript

Java

Server operating systems

FreeBSD
Linux
OS X

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux
Windows

Linux
OS X
Solaris
Windows

Linux
macOS
Windows

Data scheme

schema-free

yes

schema-free and OWL/RDFS-schema support

Typing

predefined data types such as float or date

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.

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

yes

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

Memcached protocol

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

JDBC
Native Spark Datasource
ODBC

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

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

JavaScript

Delphi
Perl
PHP

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

yes

Java

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

Using read-only observers

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

none

Shared Nothhing Auto-Sharding, Columnar Partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

Multi-source replication
Source-replica replication

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

relationships in graphs

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

caching of (temporary) tables can be configured

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

Access rights for users and roles

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