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DBMS > LevelDB vs. Sqrrl vs. TDSQL for MySQL vs. TimescaleDB vs. Tkrzw

System Properties Comparison LevelDB vs. Sqrrl vs. TDSQL for MySQL vs. TimescaleDB vs. Tkrzw

Editorial information provided by DB-Engines
NameLevelDB  Xexclude from comparisonSqrrl  Xexclude from comparisonTDSQL for MySQL  Xexclude from comparisonTimescaleDB  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
DescriptionEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesAdaptable, secure NoSQL built on Apache AccumuloA high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelKey-value storeDocument store
Graph DBMS
Key-value store
Wide column store
Relational DBMSTime Series DBMSKey-value store
Secondary database modelsDocument store
Spatial DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.35
Rank#111  Overall
#19  Key-value stores
Score0.85
Rank#205  Overall
#95  Relational DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitegithub.com/­google/­leveldbsqrrl.comwww.tencentcloud.com/­products/­dcdbwww.timescale.comdbmx.net/­tkrzw
Technical documentationgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mdwww.tencentcloud.com/­document/­product/­1042docs.timescale.com
DeveloperGoogleAmazon infooriginally Sqrrl Data, Inc.TencentTimescaleMikio Hirabayashi
Initial release20112012201320172020
Current release1.23, February 20212.15.0, May 20240.9.3, August 2020
License infoCommercial or Open SourceOpen Source infoBSDcommercialcommercialOpen Source infoApache 2.0Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaCC++
Server operating systemsIllumos
Linux
OS X
Windows
LinuxhostedLinux
OS X
Windows
Linux
macOS
Data schemeschema-freeschema-freeyesyesschema-free
Typing infopredefined data types such as float or datenoyesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data typesno
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.nonoyesno
Secondary indexesnoyesyesyes
SQL infoSupport of SQLnonoyesyes infofull PostgreSQL SQL syntaxno
APIs and other access methodsAccumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
JDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
C
C#
C++
Java
PHP
Python
Ruby
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresnonoyesuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellno
Triggersnonoyesyesno
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infomaking use of HadoopAutomatic shardingyes, across time and space (hash partitioning) attributesnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneselectable replication factor infomaking use of HadoopMulti-source replication
Source-replica replication
Source-replica replication with hot standby and reads on replicas infonone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic updates per row, document, or graph entityACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infowith automatic compression on writesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes infousing specific database classes
User concepts infoAccess controlnoCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)Users with fine-grained authorization conceptfine grained access rights according to SQL-standardno

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LevelDBSqrrlTDSQL for MySQLTimescaleDBTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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