DBMS > Google BigQuery vs. LMDB vs. Microsoft Azure Synapse Analytics vs. SAP Advantage Database Server vs. ScyllaDB

System Properties Comparison Google BigQuery vs. LMDB vs. Microsoft Azure Synapse Analytics vs. SAP Advantage Database Server vs. ScyllaDB

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

A high performant, light-weight, embedded key-value database library

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

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

Cassandra and DynamoDB compatible wide column store

Primary database model

Relational DBMS

Key-value store

Relational DBMS

Key-value store
Wide column store

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

Score	48.61
Rank	#23	Overall
	#15	Relational DBMS

Score	2.44
Rank	#117	Overall
	#22	Key-value stores

Score	20.66
Rank	#36	Overall
	#22	Relational DBMS

Score	3.68
Rank	#91	Overall
	#47	Relational DBMS

Score	3.75
Rank	#90	Overall
	#16	Key-value stores
	#8	Wide column stores

Website

cloud.google.com/bigquery

www.symas.com/symas-embedded-database-lmdb

azure.microsoft.com/services/synapse-analytics

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

www.scylladb.com

Technical documentation

cloud.google.com/bigquery/docs

docs.microsoft.com/azure/synapse-analytics

docs.scylladb.com

Developer

Google

Symas

Microsoft

Sybase, SAP

ScyllaDB

Initial release

2010

2011

2016

1993

2015

Current release

0.9.29, March 2021

Scylla Open Source 4.6, March 2022

License

Commercial or Open Source

commercial

Open Source

commercial

Open Source

Open Source (AGPL), commercial license available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Scylla Cloud: Create real-time applications that run at global scale with Scylla Cloud, the industry’s most powerful NoSQL DBaaS

Implementation language

C++

Server operating systems

hosted

Linux
Windows

Linux

Data scheme

yes

schema-free

yes

schema-free

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.

Secondary indexes

yes

cluster global secondary indices

SQL

Support of SQL

yes

SQL-like DML and DDL statements (CQL)

APIs and other access methods

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

Proprietary protocol (CQL)

compatible with CQL (Cassandra Query Language, an SQL-like language)
RESTful HTTP API (DynamoDB compatible)
Thrift

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C#
Java
PHP

Delphi
Perl
PHP

For CQL interface: C#, C++, Clojure, Erlang, Go, Haskell, Java, JavaScript, Node.js, Perl, PHP, Python, Ruby, Rust, Scala
For DynamoDB interface: .Net, ColdFusion, Erlang, Groovy, Java, JavaScript, Perl, PHP, Python, Ruby

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Transact SQL

yes

yes, Lua

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding, horizontal partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

selectable replication factor

Representation of geographical distribution of servers is possible

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Tunable Consistency

can be individually decided for each write operation

Foreign keys

Referential integrity

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

yes

Transaction concepts

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

Since BigQuery is designed for querying data

ACID

Atomicity and isolation are supported for single operations

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

caching of (temporary) tables can be configured

yes

in-memory tables

User concepts

Access control

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

yes

fine grained access rights according to SQL-standard

Access rights for users can be defined per object

More information provided by the system vendor

Specific characteristics

Scylla is a highly-available, highly-scalable, highly-performant NoSQL database....
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Competitive advantages

Highly-performant (efficiently utilizes full resources of a node and network; millions...
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Typical application scenarios

AdTech ( AdGear , AppMonet , Dstillery , FullContact , MediaMath , Numberly , SAS...
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Key customers

Comcast, Grab, OlaCabs, Yahoo! Japan, IMVU, Adgear, Xandr, Zenly, Natura, Snapfish,...
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Licensing and pricing models

Scylla Open Source - free open source software (AGPL) Scylla Enterprise - subscription-based...
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