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DBMS > Databend vs. Faircom EDGE vs. H2 vs. LevelDB vs. Splice Machine

System Properties Comparison Databend vs. Faircom EDGE vs. H2 vs. LevelDB vs. Splice Machine

Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonH2  Xexclude from comparisonLevelDB  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsFull-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.Embeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSKey-value store
Relational DBMS
Relational DBMSKey-value storeRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.34
Rank#283  Overall
#130  Relational DBMS
Score0.09
Rank#362  Overall
#53  Key-value stores
#155  Relational DBMS
Score8.33
Rank#46  Overall
#30  Relational DBMS
Score2.25
Rank#115  Overall
#19  Key-value stores
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitegithub.com/­datafuselabs/­databend
www.databend.com
www.faircom.com/­products/­faircom-edgewww.h2database.comgithub.com/­google/­leveldbsplicemachine.com
Technical documentationdocs.databend.comdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlwww.h2database.com/­html/­main.htmlgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mdsplicemachine.com/­how-it-works
DeveloperDatabend LabsFairCom CorporationThomas MuellerGoogleSplice Machine
Initial release20211979200520112014
Current release1.0.59, April 2023V3, October 20202.2.220, July 20231.23, February 20213.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infoRestricted, free version availableOpen Source infodual-licence (Mozilla public license, Eclipse public license)Open Source infoBSDOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageRustANSI C, C++JavaC++Java
Server operating systemshosted
Linux
macOS
Android
Linux infoARM, x86
Raspbian
Windows
All OS with a Java VMIllumos
Linux
OS X
Windows
Linux
OS X
Solaris
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesschema-freeyes
Typing infopredefined data types such as float or dateyesyes, ANSI Standard SQL Typesyesnoyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.noyesnono
Secondary indexesnoyesyesnoyes
SQL infoSupport of SQLyesyes infoANSI SQL queriesyesnoyes
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
JavaC++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyes info.Net, JavaScript, C/C++Java Stored Procedures and User-Defined Functionsnoyes infoJava
Triggersnoyesyesnoyes
Partitioning methods infoMethods for storing different data on different nodesnoneFile partitioning infoCustomizable business rules for partitioningnonenoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes infoSynchronous and asynchronous realtime replication based on transaction logsWith clustering: 2 database servers on different computers operate on identical copies of a databasenoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Tunable Consistency
Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infowhen using SQLyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoacross SQL and NoSQLyes, multi-version concurrency control (MVCC)yesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes infowith automatic compression on writesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.fine grained access rights according to SQL-standardnoAccess rights for users, groups and roles according to SQL-standard

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More resources
DatabendFaircom EDGE infoformerly c-treeEDGEH2LevelDBSplice Machine
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